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Full text of "Coupled-processes : interactions of contaminants, bacteria, and surfaces"

COUPLED-PROCESSES: INTERACTIONS OF CONTAMINANTS, 
BACTERIA, AND SURFACES 



By 
CHERYL A. BELLIN 



A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL 

OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT 

OF THE REQUIREMENTS FOR THE DEGREE OF 

DOCTOR OF PHILOSOPHY 

UNIVERSITY OF FLORIDA 

1993 



Copyright 1993 

by 
Cheryl A. Bellin 



ACKNOWLEDGEMENTS 

This dissertation was the collaborative effort of many people that either 
directly or indirectly facilitated the completion of this document. Working on a 
project entitled coupled processes is not easily accomplished in one laboratory 
needless to say by one individual. During the last four years I received 
assistance from many people, which I greatly appreciate. First, I would like to 
thank Dr. Suresh Rao, for his insightful method of teaching and guidance. His 
questions and discussions generated enthusiasm and challenged me to a 
higher level of thinking. I would like to thank my committee members, Drs. 
Bitton, Nkedi-Kizza, Hatfield, and Rhue for their helpful comments and 
suggestions during my doctoral program. I especially thank Dr. Bitton for 
facilitating the surface characterization of the bacterial isolates used in these 
studies and Dr. Nkedi-Kizza for his critical review of the abiotic behavior of 
quinoline. 

I would like to thank my friends and colleagues in the lab, Drs. Linda 
Lee, Denie Augustijn, Itaru Okuda, and Ms. Dongping Dai. Most of the time 
the lab was a great place to interact and work. I would like to especially thank 
Linda for her personal and professonal insight when it was asked for and even 
when it was not. I thank Ron Jessup and Gerco Hoogeweg for their modeling 



II! 



efforts. I also thank Christianne Smethurst and Ann Benner for their assistance 
in the laboratory. I give special thanks to Candace Biggerstaff who added 
levity, friendship, and help in finishing this dissertation. 

Several people in the Soil and Water Science Department have 
contributed to the work presented in this dissertation. In particular, I would like 
to thank Dr. Sylvia Coleman for her guidance and use of her laboratory for 
microbial preparations, Chris Pedersen and Dr. Amiel Jarstfer for the use of 
their laboratory and their insight on microbiology ecology, Dr. Willie Harris for an 
introduction to clay mineralogy and x-ray diffraction, and Kevin Cubinski and Dr. 
Ann Wilke for their help in designing the continuously stirred flow-through 
reactor 

I would like to acknowledge the financial support provided by the State of 
Florida via a Soil and Water Science research assistantship and additional 
funding provided through Battelle Pacific Northwest Laboratories (PNL) from the 
Department of Energy. 

I thank Dr. John Zachara and Dr. Cal Ainsworth for their insights on 
quinoline sorption, Dr. Jim Fredrickson and Dr. Fred Brockman for the bacterial 
isolates used in this study and the other Battelle PNL staff for my enhancing my 
summer fellowship experience. 

I thank my mother and father for their continued support and pride in the 
work I was doing. I also want to thank Dave Cantlin for his friendship, support, 
and patience that were essential throughout my stay at UF and in Florida. 



IV 



TABLE OF CONTENTS 



ACKNOWLEDGEMENTS ^ 

LIST OF TABLES 

VII 

LIST OF FIGURES vijj 

ABSTRACT 

XI 

CHAPTERS 

1 INTRODUCTION 1 

Overview of the Problem -I 

Sorption -, 

Biodegradation g 

Transport 18 

Research Objectives 21 

2 CHEMODYNAMICS OF N-HETEROCYCLIC COMPOUNDS IN 
ABIOTIC SYSTEMS: BATCH AND FLOW-THROUGH 
TECHNIQUES 25 

Introduction 25 

Quinoline Sorption Dynamics 28 

Research Question and Tasks .".".'" 35 

Materials and Methods '.'.'.'. 35 

Results and Discussion 3g 

Summary 73 

3 ALTERATION OF SURFACES BY BACTERIAL BIOMASS .... 75 

ft. 

Introduction 75 

Research Question and Tasks 78 

Materials and Methods '.'.'.'.'. 79 

Results 83 

v 



Discussion 98 

Summary 101 

4 QUINOLINE BIODEGRADATION IN FLOW-THROUGH 
SYSTEMS 103 

Introduction 103 

Quinoline Biodegradation Dynamics 121 

Research Question and Tasks 126 

Material and Methods 127 

Results and Discussion 132 

Summary 145 

5 SUMMARY AND CONCLUSIONS 148 

Summary 148 

Conclusions 154 

REFERENCES 157 

BIOGRAPHICAL SKETCH 170 



VI 



LIST OF TABLES 

Table page 

2-1. Soil properties before and after steam autoclaving 36 

2-2. Column parameters for sterile soil columns 48 

2-3. Summary of estimated transport parameters for quinoline 57 

3-1. Column parameters and Kj values for quinoline, naphthalene, and 

45 Ca in sterile and inoculated Norborne soil columns 87 

4-1. Nutrient concentration (mg/L) extracted from the Norborne soil 

column 133 



VII 



LIST OF FIGURES 



Figure page 

2-1. Calcium <p) and quinoline (o) BTCs: a) pH 6, v = 0.162 cm/s and 
b) pH = 6.9, v = 0.063 cm/s. Lines correspond to equilibrium 
(solid) and first-order models (dash), (from Szecsody and Streile, 
1992) 27 

2-2. Quinoline speciation diagram and the protonated and neutral 

species structures 29 

2-3. Quinoline sorption isotherms for three soils normalized to their 
cation exchange capacity and to the fraction of protonated 
species 41 

2-4. Stirred batch reactor (a) and quinoline sorption onto the Norborne 
soil fraction < 50/um (b) (where C = quinoline filtrate 
concentration and C = the initial quinoline concentration) 43 

2-5. Sorption of quinoline on the Norborne soil in the presence of 2- 

hydroxyquinoline 44 

2-6. Examples of breakthrough curves for PFBA and 3 H 2 in Norborne 

soil columns 46 

2-7. Quinoline and 45 Ca breakthrough curves with flow interruptions in 
0.005 M (closed symbols) and 0.05 M (open symbols) CaCI 2 
Norborne soil columns 49 

2-8. Quinoline breakthrough curves in 0.005 M (closed symbols) and 
0.05 M CaCI 2 (open symbols) in pH adjusted Norborne soil 
columns 51 

2-9. Repeated flow interruptions for quinoline in a 0.05 M CaCI 2 (pH 

6.2) Norborne soil column and bicontinuum model fit 55 



VIII 



2-10. Conceptual diagram of quinoline sorption onto smectite clay 

minerals 60 

2-11. Isotopic exchange of 12 C-quinoiine and 14 C-quinoline in 0.05 M 

CaCI 2 (pH 6.2) in the Norborne soil 63 

2-12. Breakthrough curves of quinoline in Eustis soil with 0.005 M CaCI 2 

and 30% methanol 67 

2-13. Structural representation of organic matter (adapted from Behar 

and Vandenbroucke, 1987) 69 

2-14. Scanning electron micrograph of an organic soil at 6000 x and 

1000 x 72 

3-1. Measured BTCs for PFBA (H) in a sterile column and for Quinoline 
in a sterile (•), 3N3A inoculated (*), and B53 inoculated (□) soil 
column. Column designations are given in parenthesis 
corresponding to Table 3-1 84 

3-2. Measured BTCs for 45 Ca in sterile (•) and B53 inoculated (o and 
*) soil columns. Column designations are given in parenthesis 
corresponding to Table 3-1 85 

3-3. Measured BTCs for Naphthalene in a sterile (•) and a B53 
inoculated (O) soil column. Column designations are given in 
parenthesis corresponding to Table 3-1 86 

3-4. Measured BTCs for PFBA (*), 45 Ca (•), Quinoline (□), and 

Naphthalene (o) in a B53 inoculated soil column 92 

4-1. Schematic of sorption and biodegradation in soil aggregates (C 
and C = the solute concentration in the pore water inside the 
aggregate and the bulk solution, respectively) (adapted from 
Mihelcic and Luthy, 1988c) 106 

4-2. The impact of varying the sorption partition coefficient on 

biodegradation (L/kg) in the presence of aggregates with radii of 

0.05 cm. (From Scow and Hutson, 1992) 108 

4-3. Data (symbols) for aggregates with different radii and DSB model 
simulations (solid lines) of mineralization of 50 ng 14 C-labeled 
glutamate/mL in the presence of gel exclusion beads. (From Scow 
and Alexander, 1992) 109 



IX 



4-4. Measured and simulated BTCs for 2,4,5-T developed with the two 
region model for the two cases of no degradation (m =0) and 
degradation (m>0). (From Gamerdinger et al., 1990) 111 

4-5. Simulation of naphthalene degradation in soil suspensions. The 
lines were generated using the bicontinuum model with first order 
biodegradation kinetics, (model input parameters from Guerin and 
Boyd, 1992) 113 

4-6. Simulation using the bicontinuum model with first-order 

biodegradation kinetics assuming irreversible sorption 115 

4-7. Naphthalene mineralization for strain NP-Alk in a soil free (o), 

Colwood (a) and Oshtemo (b) soil slurries with 66.7 (•), 133 p), 

or 200 (B) mg/mL (From Guerin and Boyd, 1992) 116 

4-8. Naphthalene mineralization time courses for strain 17484 in a soil- 
free control and Capac (a) and Colwood soil suspensions (From 
Guerin and Boyd, 1992) 117 

4-9. Conceptualization of quinoline biodegradation in the presence of 

smectite clay minerals 122 

4-10. Schematic of CSFTR system used to monitor quinoline 

biodegradation 129 

4-11. Quinoline biodegradation in a Norborne soil column with limiting 

nutrients 137 

4-12. Biodegradation of quinoline and production of 2-HQ by the 3N3A 

isolate in the CSFTR 140 

4-13. Alteration of bacterial activity upon introduction of Norborne clay 

and silt as measured by the change in biodegradation of quinoline. 142 



Abstract of Dissertation Presented to the Graduate School 
of the University of Florida in Partial Fulfillment of the 
Requirements for the Degree of Doctor of Philosophy 

COUPLED PROCESSES: INTERACTIONS OF CONTAMINANTS, 
BACTERIA, AND SURFACES 

By 

Cheryl A. Bellin 

August 1993 

Chairperson: P.S.C. Rao 

Major Department: Soil and Water Science 

Bioavailability and biodegradation of organic solutes in soils are 

thought to be controlled by coupled sorption and transformation processes. 

The principal hypothesis is that sorbed substrates are unavailable to 

microorganisms. The fact that microorganisms may actively change the local 

environment further complicates the issue by altering the magnitude and 

kinetics of sorption and degradation. The importance of coupled sorption- 

biodegradation processes is recognized in regard to the impact on 

environmental contamination and bioremediation. 

Bioremediation technologies have generally had limited success in 

achieving adequate levels of cleanup, primarily because of constraints on 

bioavailability of sorbed contaminants. Thus, understanding the interactions 



Xi 



among sorption, biodegradation, and transport processes is needed to 
elucidate rate-limiting mechanisms of contaminant biodegradation. 

Quinoline, an ionizable organic base, is a contaminant of interest found in 
energy-derived waste materials and products. Batch reactors were used to 
measure quinoline equilibrium sorption coefficients in the absence of physical 
constraints. Miscible displacement studies were conducted to simultaneously 
measure quinoline sorption and biodegradation. The quinolinium cation was the 
predominant species sorbed via cation exchange. However, the bicontinuum 
sorption nonequilibrium model was inadequate in describing the measured 
breakthrough curves for quinoline displacement through "sterilized" soil 
columns. Quinoline-surface complexes limit the desorption and redistribution 
within the sorbent matrix and thus, are likely to be unavailable for degradation. 

Addition of bacteria (quinoline-nondegrader) reduced quinoline sorption 
and retardation in soil columns, which were attributed to biomass-induced 
changes in quinoline speciation and blockage of surface sites. In columns 
inoculated with a quinoline-degrader, quinoline was rapidly degraded and 
biodegradation kinetics could not be measured. The continuously stirred flow- 
through reactor was used as an alternate technique to monitor rapid 
biodegradation kinetics (k b < 0.5 seconds" 1 ) and to measure the response to 
imposed perturbations. Introduction of sorbent particles at steady state (i.e., 
biodegradation of quinoline to 2-hydroxyquinoline and other metabolites) 
resulted in two responses: 1) addition of soil particles required readaptation of 
the bacterial isolate and caused reduced degradation rates; and 2) soil particles 

xii 



reduced 2-hydroxyquinoline uptake and degradation, while quinoline 
biodegradation was not altered. In this case, bacterial activity may have been 
reduced upon bacteria-sorbent association. 



XIII 



CHAPTER 1 
INTRODUCTION 



The motivation for this dissertation arose from my desire to work with 
microorganisms and to determine their potential for bioremediation of 
contaminated soils, aquifers, and sediments. There is an illusion that bacteria 
are fragile, delicate creatures. The reality of the situation, after working with 
them for the last few years, is that they at times seem to have a mind of their 
own. They have the capability to alter their environment in order to enhance 
their very existence. I believe that their potential in bioremediation practices is 
unlimited if we can only come to understand how they interact with their 
environment. As Marshall (1976) stated: 



It is my belief that many microbiologists fail to appreciate the effects of 
interfaces on microbial populations, despite the widespread occurrence 
of solid-liquid, gas-liquid, and liquid-liquid interfaces in natural microbial 
habitats. . . . Importance must be given to the nature, distribution, and 
unique physicochemical properties of interfaces, the interaction between 
microorganisms and interfaces, and the modifying effects of interfaces on 
the ecology of microorganisms, (v) 



Overview of the Problem 
The improper use and accidental release of toxic organic compounds 
into the environment have led to widespread contamination of soils and 

i 



aquifers. Treatment of contaminated materials has included excavation, 
incineration, vapor extraction, and soil washing technologies. These treatments 
are often costly and only result in a transfer of the contaminant from one phase 
to another. However, implementation of above ground and in situ 
bioremediation practices may lead to degradation of organic contaminants. 

Bioremediation practices using laboratory tested microbial populations 
have failed to achieve adequate levels of cleanup for reasons which will be 
discussed. Failures are not surprising because frequently laboratory studies 
investigate processes in isolation and attempt to extrapolate to field sites where 
temperature, pH, soil water content, and microbial populations vary daily and 
seasonally. As Rao et al. (1993a) so accurately described: 



Most laboratory-scale experiments, and some field-scale studies, are 
designed for investigating environmental processes in isolation; at least 
attempts are made to do so by controlling most variables except the one 
whose impact upon the system is being investigated. In real-world 
scenarios, even in the simplest of laboratory experiments, however, the 
rates and magnitudes of a reaction or a process are often controlled by 
one or more other processes, each of which may have its own set of 
unique control variables at different spatial and temporal scales. This is 
indeed the case for laboratory experiments and field studies on fate and 
transport of organic chemicals in soils and aquifers. An explicit 
understanding of the coupling and feedback among simultaneous 
processes is essential in explaining experimental observations and for 
developing predictive models. (1) 



To illustrate the importance of process coupling, Rao et al. (1993a) 
presented two different scenarios. In one case, sorption renders the 
contaminant unavailable for biodegradation and in the second case 



3 
biodegradation is unaffected by sorption. The first example suggests that 

differences in biodegradation may be due to the soil sorption capacity and/or 

variations in microbial activity. The second example suggests that differences in 

biodegradation are due solely to variations in microbial activity and bioavailability 

(sorption of contaminants) is not a factor. 

The use of bioremediation technology is hinged upon improving existing 
knowledge of the controlling processes and their appropriate coupling such that 
the probability and predictability of remediating a contaminated site are 
increased. To fulfill this task it is necessary to 1) determine the reasons for 
bioremediation failures; 2) develop predictive coupled-process models for 
describing contaminant fate in the environment; and 3) determine the 
ramifications of introducing bacteria or stimulating bacterial growth in soil and 
aquifer materials to promote biodegradation of contaminants. 

The success of bioremediation of contaminated soils and groundwater is 
limited due to (1) the ability to degrade chemicals to an acceptable level and (2) 
the ineffectiveness of laboratory-tested microorganisms to biodegrade 
chemicals under field conditions. Understanding the physical and chemical 
constraints of biodegradation in soils and aquifers may improve the designs of 
bioremediation programs and provide an understanding of the reasons for 
chemical persistence. Therefore, information is needed regarding microbial 
transformations of organic chemicals in soil-water systems, as affected by the 
interaction of chemical, physical, and biological processes. 



4 

A lack of consideration of physico-chemical and biological processes can 
result in discrepancies between model predictions and experimental 
observations. Investigation of organic chemical behavior in natural systems 
and development of solute transport models that account for biodegradation 
and sorption are necessary to adequately predict the environmental behavior of 
such chemicals. These models can then be used to gain insight into the 
processes that affect the fate of chemicals in the environment, for prescribing 
management strategies that prevent or minimize groundwater contamination, 
and for designing effective remediation procedures for contaminated sites. 

Coupled-process models attempt to describe contaminant sorption, 
degradation, and water flow by incorporating pertinent processes controlling the 
fate of contaminants. Mathematical descriptions of existing coupled-process 
models were reviewed by Brusseau et al. (1992). Development of an unbiased 
coupled-process model requires a multidisciplinary approach. However, models 
often contain a particular emphasis on a single process depending on the 
researcher's background. The conceptual basis for the coupling of sorption 
and biodegradation during transport was presented by Rao et al. (1993b). 
Emphasis was given to the importance of adequately describing contaminant 
sorption and the impact of the biomass on contaminant behavior. 

Various levels of complexity arise when describing the processes that 
control contaminant behavior. Frequently models are limited by the ability to 
accurately measure the parameter of interest. When dealing with aquifer 



5 
materials, steady water flow is assumed. However, the unsaturated zone adds 

seasonal variations in soil water content and temperature which directly or 

indirectly impact the primary processes controlling the fate of contaminants. A 

description of the sorption dynamics is primarily concerned with equilibrium or 

rate-limited reactions, whereas microbial processes require descriptions of 

microbial kinetics (e.g., growth and biodegradation) and biomass distribution. 

Extensive data have been gathered describing individual processes that 
determine the behavior of hydrophobic organic compounds (HOCs). 
Equilibrium sorption coefficients (K p ) for HOCs can be estimated from aqueous 
solubility and octanol-water partition coefficients among others (cf., Green and 
Karickhoff, 1990; Gerstl, 1990). The sorption mass-transfer coefficients (k 2 ) can 
be estimated for a variety of soils and HOCs from the inverse, log-log 
relationship noted between k 2 and K (Brusseau and Rao, 1989a) or K„„ 
(Augustijn, 1993). Specific interactions between ionizable organic acids and soil 
caused deviations from the behavior of HOCs (Brusseau and Rao, 1989a). 
Complex sorption interactions of organic bases such as the nitrogen 
heterocyclic compounds (NHCs) in soil have not been adequately investigated 
to assess if this relationship is valid for NHCs. 

The estimation of the model parameters related to biomass growth 
dynamics of specific degraders and substrate degradation kinetics in soil and 
aquifer materials is somewhat uncertain. Monod-type equations are used to 
describe the behavior of pure culture systems. However, these models did not 



6 
adequately describe degradation in mixed culture laboratory systems (Scow et 

al., 1986; Simkins et al., 1986). Therefore, these models are not likely to predict 

field-scale observations. Blackburn (1989) claims that laboratory-scale 

predictions of field-scale observations are destined to fail because of the 

complexity of the spatial scales of interest (for further discussion see Rao et al., 

1993a). Blackburn (1989) suggested that the Heisenberg Uncertainty Principle 

applies to microbial dynamics which states that by simply making an 

experimental observation (since most experimental techniques are invasive, 

though in some cases noninvasive techniques may be used), the system is 

perturbed and is no longer an adequate representation of the original system. 

Despite these arguments, complex degradation models have been developed 

that incorporate availability of electron acceptors and electron donors, nutrients, 

and the oxygen status in aquifers (Widdowson et al., 1987; 1988; MacQuarrie 

and Sudicky, 1990). Because of the inability to describe the parameters at the 

field scale, many of these models are not validated. 

Existing coupled process models are highly limited by a lack of 

experimental observations (laboratory and field scales) that quantitatively 

demonstrate the effects of process coupling, specifically the manifestation of 

such coupling on contaminant migration/degradation rates and profiles. 

Laboratory studies coupling sorption, degradation, and transport are limited to 

HOCs; most are conducted in batch reactors. The simultaneous sorption, 

transformation, and transport of NHCs in dynamic soil systems has not been 



7 
studied. NHCs can exist in their protonated or neutral form depending on the 
pH in the system. Therefore, to estimate the fate of these compounds, an 
adequate representation of the appropriate linkages between the controlling 
processes is essential. For these compounds, variations in pH will have 
ramifications on the microbial community and their activity as well as on the 
sorption dynamics. The following section is a review of the key processes that 
control the fate of organic compounds and discuss the factors important in 
developing a coupled- process model. 

Sorption 
The distribution of HOCs between the solid and solution phases is 
characterized by an equilibrium sorption partition coefficient (Karickhoff et al., 
1979; Chiou et al., 1983). Most often the Freundlich isotherm is used: 

where S is the sorbed concentration (^g/g), Kf = Freundlich sorption coefficient 
[ m i_(i/n) |ug[ 1 ~( 1 / n) tyg], C = equilibrium solution concentration (jug/mL), and 1/n 
= Freundlich isotherm constant. Equilibrium sorption models are often used in 
solute transport models. However, equilibrium assumptions are generally 
inadequate in describing local-scale and field-scale sorption because 
nonequilibrium conditions predominate. 

Sorption nonequilibrium for HOCs can be described using the 
bicontinuum model (Brusseau and Rao, 1989b). Conceptually, the model 



8 
describes partitioning of compounds into the soil organic phase or adsorption 

of compounds onto surfaces. Nonequilibrium sorption is represented by a two- 
step process in which sorption in the first domain is instantaneous, while mass 
transfer constraints limit sorption in the second domain. Thin organic coatings 
distributed throughout the soil may result in minimal constraints for sorption 
mass transfer, whereas sorption into large organic particles may increase solute 
diffusion due to limited accessibility of sorptive regions. Factors that limit the 
rate of HOC sorption that have been proposed include intraparticle diffusion 
(IPD) (Wu and Gschwend, 1986; Ball and Roberts, 1991) and intraorganic 
matter diffusion (IOMD) (Brusseau et al., 1991). Regardless of the actual 
mechanism responsible for rate-limited sorption, contaminants are likely to 
reside within the interior regions of the sorbent matrix. The consequences of 
this occurrence on biodegradation will be discussed in the next section. 
Sorption of NHCs has been described by the Freundlich isotherm 
(Zachara et al., 1986, Ainsworth et al., 1987). Linearity of the sorption 
isotherms varied, approaching a linear isotherm at low concentrations and 
surface coverages (Ainsworth et al., 1987). The protonated species is the 
predominant form of NHCs sorbed and is expected to sorb primarily onto cation 
exchange sites. These sites may be associated with phyllosilicate minerals or 
organic matter. In either case, sorption is likely to be rate limited due to 
migration into clay interlayers and aggregates or organic matter matrices. 
Given the complexity of exchange reactions involving organic cations, the 



9 
bicontinuum model may not adequately describe the behavior of NHCs in soil 

materials. This aspect will be explored further in a later section (see Chapter 2). 

Biodegradation 
Bioavailability 

Biodegradation is a dominant mechanism affecting organic chemical 
transformations in soils and aquifers. Microbial degradation of most small 
organic compounds (molecular mass < 600) occurs intra-cellularly (Bitton et al., 
1988). Thus, the rate of biodegradation is limited by the dynamics of 1) 
physical-chemical processes (e.g., solubility, sorption, hydrodynamic dispersion) 
that leads to a lowering of solute concentration in the solution phase; 2) soil or 
environmental factors that limit physiological activity of the appropriate microbial 
consortia; 3) microbial factors that limit substrate uptake by the microorganisms 
(e.g., cell permeability and hydrophobicity); and 4) intra-cellular genetic or 
biochemical factors (e.g., presence of appropriate enzyme systems, presence 
and expression of genes) that limits utilization of the compound. The 
recalcitrance of different organic chemicals in a specific soil, or the variations in 
degradation rates of a specific compound in several soils, may be explained to 
a large extent by understanding these key factors. 

Inoculation of soils and aquifers with microorganisms capable of readily 
degrading chemicals may result in a partial or complete lack of contaminant 
removal due to various environmental stresses not present under laboratory 
conditions. Contaminant persistence may result from the following factors 



10 
(Madsen, 1985; Goldstein et al., 1985): 1) low substrate concentrations not 

supporting microbial growth; 2) microorganisms encountering toxins or 

predators; 3) microorganisms using more readily available carbon sources; and 

4) introduced microorganisms not reaching the contaminated site. 

Enhanced on-site or in-situ biodegradation provides a method for 
removing organic contaminants in soils and aquifers. Utilizing indigenous 
microorganisms is preferable to "inoculation" or injection because they are 
already adapted to the local environment. However, in the subsurface 
environment, the complex interaction between microorganisms, substrates, and 
surfaces may alter this process. Biodegradation rates may be limited by 
chemical properties of substrates, interactions of the substrate with surfaces, or 
simply by the lack of necessary enzymes (Madsen, 1985). Availability of slightly 
soluble substrates may be controlled by the rate of dissolution (Stucki and 
Alexander, 1987; Miller and Bartha, 1989; Huang and Chou, 1990), or by low 
aqueous concentrations which may not induce the necessary enzymes for 
biodegradation (Madsen, 1985). Similarly, sorption of the substrate by soil may 
reduce substrate concentrations in solution below levels necessary for enzyme 
induction. 

Sorption of substrates might also enhance biodegradation rates by 
decreasing the substrate concentration to levels that are not toxic to 
microorganisms responsible for degradation (van Loosdrecht et al., 1990). 
Sorption more likely reduces or inhibits biodegradation rates in soils (Stotzky 



11 

and Rem, 1966; Madsen, 1985; van Loosdrecht et al., 1990). For example, 
sorption was found to decrease the amount of substrate available to 
microorganisms capable of degrading several compounds, including diquat 
(Weber and Coble, 1968), benzylamine (Subba-Rao and Alexander, 1982; Miller 
and Alexander, 1991), alkylamines (Wszolek and Alexander, 1979), glucose 
(Gordon and Millero, 1985), 2,4-Dichlorophenoxyacetic acid (Ogram et al., 
1985), amino acids (Dashman and Stotzky, 1986), toluene (Robinson et al., 
1990), benzidine (Weber, 1991), quinoline (Smith et al., 1992), and flumetsulam 
(Lehman et al., 1992). Degradation was adequately described by a second- 
order rate equation with the assumption that only solution-phase chlorproham 
and dibutyl phthalate are biodegraded in the presence of sediments (Steen et 
al., 1980). 

Biodegradation of contaminants may be limited when contaminants are 
sequestered within the organic or inorganic components of the sorbent matrix 
that are not directly accessible to microorganisms. Biodegradation may also 
be limited by mass transfer (IPD and IOMD) from the interior of the sorbent to 
the exterior solution. Bioavailability is limited in these examples because intra- 
aggregate pores are too small to be accessible to bacteria (Steinberg et al., 
1987, Scow and Alexander, 1992). The substrate sorbed within organic matter 
is accessible only after desorption or diffusion out of the sorbent matrix. Mass 
transfer constraints have been shown for sorption/desorption of hydrophobic 
organic compounds (HOCs) in soils and sediments (Wu and Gschwend, 1986; 



12 
Brusseau and Rao, 1989b; Brusseau et al., 1991), for biodegradation of HOCs 

(Rijnaarts et al., 1990; Robinson et al., 1990), and for denitrification (Myrold and 

Tiedje, 1985). For naphthalene, which exhibits reversible sorption/desorption 

(Mihelcic and Luthy, 1988a,b), biodegradation was not dependent upon 

desorption kinetics from fine-sized material (Mihelcic, 1988). For larger 

particles, biodegradation of naphthalene was dependent upon intra-particle 

diffusion from the solid-phase to the solution-phase, which suggests mass 

transfer constraints or reduced bioavailability of the sorbed naphthalene 

(Mihelcic and Luthy, 1988c). 

For quinoline, highly selective cation exchange reactions may control 

mass transfer from the soil to solution, thereby limiting biodegradation. Smith et 

al. (1992) suggested that biodegradation of quinoline in dispersed clay 

suspensions is limited by desorption of the highly stable quinolinium ion surface 

complex. However, it is not known if these same rate-limiting steps control 

biodegradation rates in soils and sediments or if diffusion-limited mass transfer 

constraints (IOMD, IPD) are operative. For this reason, mechanistic models 

coupling the sorption, degradation, and transport in soil and aquifer systems 

are needed to understand the rate-limiting steps of organic chemical 

biodegradation. 

Effects of Surfaces on Biodegradation 

At the cellular-scale, the influences of surfaces on bacterial activity have 
been monitored indirectly in a variety of disciplines. Reported observations 



13 

suggesting the influence of surfaces on bacterial activity have been dismissed 

because of possible secondary responses occurring at the surfaces (van 
Loosdrecht et al., 1990). Ogram et al. (1985) demonstrated that sorbed 2,4- 
dichlorophenoxy acetic acid (2,4-D) was protected from biodegradation and that 
only the solution-phase 2,4-D was degraded by free and attached bacteria. The 
degradative activity of free and attached bacteria, however, could not be 
differentiated. In a similar study, 2,4-D was suggested to be degraded by 
bacteria in the sorbed and solution phase (Zou et al., 1992); however, 
degradation rates were thought to be faster by "free" bacteria rather than 
sorbed-phase bacteria. Aamand et al. (1989) also suggested that only bacteria 
in the solution phase were degrading the aquifer contaminants. 

More recently, Guerin and Boyd (1992) argued that a bacterial isolate (P. 
putida 17484) was capable of utilizing sorbed naphthalene from the surface, 
contrary to the paradigm that degradation occurs intracellular^. Another 
bacterial isolate (NP-Alk) was thought to be unable to degrade naphthalene in 
the sorbed- phase. Therefore, organism-specific properties must be considered 
in determining the potential for degradation. These observations will be 
discussed further in Chapter 4. Determining the influence of surfaces on 
biodegradation and whether or not bacteria have the ability to degrade 
contaminants in the sorbed or solution phase is still unresolved. Further, a 
predictive model requires knowledge of the distribution of the active microbial 
biomass and microbial growth dynamics (e.g., contingent upon substrate, 



14 
nutrient, and electron acceptor concentration and bacterial population) in 

combination with factors discussed above. 

Biomass Distribution 

Microbial biomass is subject to sorption and transport processes. 
Therefore, bacteria may exist in the soil either sorbed (attached) or in solution 
(free). Physical, chemical, and microbial factors controlling the distribution of 
bacteria in porous media have recently been summarized by Harvey (1991), 
Lindqvist and Enfield (1992b), and Tan et al. (1992). Bacteria grow after they 
attach to surfaces if essential carbon and energy sources are available. Growth 
and development of bacterial colonies generally is followed by the production of 
extracellular polysaccharides and promote the formation of bacterial biofilms 
(van Loosdrecht et al., 1990; Fletcher, 1991). Under nutrient- and substrate-rich 
conditions, as may be the case near waste disposal sites, biofilms may be 
formed. 

Mathematical models for biodegradation are developed assuming that 
the microbial biomass may be distributed in biofilms, microcolonies, or uniformly 
throughout the porous medium (Baveye and Valocchi, 1989). The assumption 
of microbial biofilms suggests that surfaces are uniformly coated by biofilms in 
which the degradation of the contaminant and the utilization of the electron 
acceptor takes place (Rittman and McCarty, 1980). The microcolony approach 
suggests that bacteria exist in discrete microcolonies and that growth and 
substrate utilization rates correspond to the microbial population (Molz et. al., 



15 
1986; Marshall, 1992). Recent microscopic evidence suggests that bacteria 

exist in microcolonies with bacterial cells extending out into the soil pore spaces 

(Vandevivere and Baveye, 1992). The difficulty in mathematically describing the 

dimensions of the biofilms and microcolonies limits the utilization of these 

models in soils and aquifers. The uniform microbial description, commonly 

used in solute transport models, makes no assumptions about the distribution 

of bacteria (e.g., discrete colonies or biofilms) in solution or on the surfaces 

(Corapicoglu and Haridas, 1985; Kindred and Celia, 1989). This concept 

suggests that overall growth and metabolism are not influenced by the microbial 

distribution. 

Biomass Impacts on Contaminant Sorption and Transport 

Growth or addition of bacteria may drastically alter the chemical, physical 
and microbiological environment of soil surfaces (Fletcher, 1991). Chemical 
properties of soil surfaces may be altered by bacterial biomass thereby 
influencing contaminant transport (Stucki et al. 1992; van Loosdrecht et al., 
1990; Stotzky, 1966). Physical alterations including blockage of pores by 
bacterial biomass and blockage of sorptive regions in the soil may occur 
altering water flow and sorption contaminants (Tan et al., 1992; Vandevivere 
and Baveye, 1992). Bacterial transport (e.g., solution phase bacteria) and their 
facilitation of contaminant migration was recently demonstrated (Lindqvist and 
Enfield, 1992a). The impact of bacterial biomass is becoming recognized as an 
important process influencing contaminant sorption and transport (Rao et al., 



16 

1993b). Therefore, the impact of bacterial biomass near hazardous waste sites 

is of interest. 

Environmental Factors Influencing Biodegradation 

Environmental variables may be significant in surface soils where 
microbial communities are in direct contact with the soil atmosphere. Seasonal 
cycles in temperature and soil-water content distinguish this zone from aquifer 
systems that may exhibit more constant conditions. Groundwater temperatures 
are relatively constant; however, temperatures may be as low as 10 to 15°C 
which may reduce microbial activity. Surface fluctuations in temperate regions 
may reduce bacterial activity throughout the winter months. In contrast, 
bacterial activity will likely be high in warmer, tropical environments. Variations 
in temperature over the usual range of interest (5-40°C) are not likely to 
influence the degradation pathway, only the rate of microbial degradation and 
the microbial density. Changes in soil-water content, on the other hand, may 
influence microbial communities and their activity. 

Quantitative and qualitative differences result when observing aerobic and 
anaerobic degradation. Deep, saturated aquifers may be depleted in oxygen 
and bacterial populations may be limited by the availability of alternate electron 
acceptors (N0 3 , S0 4 , C0 3 ). In oxygen depleted zones, fermentation results in 
incomplete degradation of contaminants. Flow heterogeneities may create 
zones of mixing thus supplying adequate nutrients and cofactors to stimulate a 
diverse and numerous group of microorganisms. On the other hand, a 



17 

contaminated area can turn an oxygenated aquifer into an anoxic region, if the 

heterotrophic respiration exceeds oxygen input or recharge. In well-drained 
soils and shallow aquifers, microbial populations are predominantly aerobic, 
utilizing gaseous or dissolved oxygen as an electron acceptor which would 
degrade organic contaminants to metabolites and ultimately mineralized to C0 2 , 
H 2 0, and other elements. Even in a well-drained soil, however, anaerobic 
regions (e.g., microsites) may develop as oxygen is depleted potentially altering 
the end products of metabolism. 

Biodearadation Models 

Specific growth rates of microbial populations have been represented by 
a variety of mathematical models (Pirt, 1975; Alexander and Scow, 1989; Bazin 
and Menell, 1990). The empirical power rate model: 

^ - -*bC n (1-2) 

where k b is the biodegradation rate constant (1/T), simplifies to a first-order 
kinetics model when n = 1 (Hamaker, 1972). Concern over the use of this 
model is expressed as it is often presented with no theoretical justification for its 
use (Bazin et al., 1976). 

The description of the microbial growth rate when it is restricted by the 
concentration of a growth-limiting substrate is given by the Monod equation 
which was developed from enzyme kinetics: 



18 

M " Mmax[ KT71J ] (1 " 3) 

where y is the specific growth rate of the biomass (1/T), /z max is the maximum 
specific growth rate (1/T), S is the substrate concentration (M/L 3 ) and K is the 

o 

substrate half saturation constant (M/L 3 ). This equation is commonly used to 
describe the bacterial growth upon contaminant degradation. 

Often, organic contaminant degradation is limited by availability of an 
electron acceptor or an additional carbon substrate. The modified Monod 
equation couples the dependence of bacterial growth on another carbon 
substrate or electron acceptor: 

„ - M max [-jjfg] [^] (1-4) 

where O is the oxygen concentration (M/L 3 ) and K is the oxygen half 
saturation constant (M/L 3 ). Equations may also incorporate an inhibition 
coefficient to account for growth rate limitations due to a toxic feedback 
mechanism (Harvey and Widdowson, 1992). In order to adequately describe 
contaminant behavior, all parameters necessary for these models must be 
measured at the particular scale of interest. 

Transport 
The governing differential equation that serves as the basis for most 
coupled-process models used in soils and aquifers is 



19 

*S2 - [V • D8 Vq - [V • qC\ - [ifeS] ±2>, (1-5) 

where C = solution-phase concentration (M/L 3 ); S = sorbed-phase 
concentration (M/M); t = time (T); p = soil bulk density (M/L 3 ); 6 = fractional 
volumetric water content (dimensionless); D = hydrodynamic dispersion 
coefficient (L 2 /T); x = distance (L); q = Darcy flux for water flow (L/T); and </>■ 
= rates (M/L T) of loss or gain via various sinks and sources. In Eq (1-5), 
multi-dimensional, advective-dispersive solute transport in a heterogeneous 
porous medium under transient water flow conditions (first two terms on the 
r.h.s.) is coupled to sorption dynamics (third term on r.h.s.) and biodegradation 
kinetics (last term on r.h.s.). Differences in published models arise from the 
specific manner in which sorption and degradation kinetics are modeled, 
whether transient or steady flow is considered, and if one- or multi-dimensional 
transport is of interest. 

For one-dimensional steady, saturated water flow conditions in a 
homogeneous medium, eq (1-5) can be restated as 

at ex 2 dx e at e^ ' 

where v=(q/6) is the average pore-water velocity (L/T). 

Assuming that sorption can be represented by the bicontinuum sorption 
model with a Freundlich isotherm and that first-order biodegradation kinetics 
apply to biodegradation (0 = - k b 8C), eq (1-6) is restated as follows: 



20 



[1 + £F/^] *&1 - D^ - v*£ - £ £* - /c b C (1-7) 



where k b represents the pseudo first-order rate constant (1 /T) for 
biodegradation (assumed to occur only in the solution phase), Kf is the 
Freundlich sorption coefficient (mL (1/n) Aig [1 " (1/n)] /9). and 1/n is the Freundlich 
sorption isotherm coefficient. Note that the Freundlich model (eq 1-1) is used 
to represent equilibrium sorption isotherms. Thus, isotherm nonlinearity may be 
accounted for with this model which results in nonlinear mass transfer and 
mixed order (1/n) equations. The model may be written in nondimensional 
form (Nkedi- Kizza et al., 1989): 



*°- + (/?fl-1)(1/n)C*( 1 /n)-1^ 
dp dp 



i* 



p dX 2 dx P) dp 



(1-/3) /?^51 - co (C*( 1 /n)_ s *) (1-8b) 

dt V ' 

by defining the following dimensionless parameters: C* = C/C , p = vt/L, X = 
x/L, Y = kv/L, S* = [Sa/d-FJKfC^/nH], R = [1 + ( (p /e) K^ 1 /"*" 1 )] is the 
retardation factor, which represents equilibrium sorption; P = vL/D is the Peclet 
number, which represents the hydrodynamic dispersion in the column; 
j8 = {[1 + (Fp/ejKjC^/^'^/R} represents the fraction of instantaneous 



21 
retardation; co = {[k 2 (1-/3)RL]/v} is the Damkohler number, which is 

proportional to the ratio of hydrodynamic residence time (L/V) to the reaction 
time (1/k 2 ); L is the length of the column (L); F is the fraction of sorption in the 
instantaneous regions; k 2 is the first-order rate coefficient (1/T). 

At the field scale, heterogeneous flow fields are often assumed to be 
represented as being macroscopically homogeneous (MacQuarrie and Sudicky, 
1990). The effects of local-scale pore-velocity variations are represented by a 
"macrodispersion" term for the whole flow field. MacQuarrie and Sudicky (1990) 
showed that such an approach can lead to a serious overestimation of 
substrate degradation rate as a result of far greater mixing of the substrate and 
dissolved oxygen plumes predicted to occur at the local scales when a macro- 
dispersion concept is employed. This is a clear demonstration of the 
importance of appropriately understanding local-scale physical heterogeneity in 
explaining and predicting macro-scale observations of biodegradation. 
Similarly, heterogeneities in the flow fields may create mixing zones where high 
concentrations of electron donors (i.e., organic acids produced by fermentation 
processes active in oxygen limited regions) and acceptors (i.e., oxygen) create 
high microbial populations and degradation capacities. 

Research Objectives 
Over the past two decades, studying each factor that influences the 
environmental behavior of organic chemicals in isolation has resulted in the 
accumulation of an extensive database on several key processes. As Rao et al. 
(1993a) pointed out: 



22 



Having made impressive advances in our understanding of the key 
processes (transport, transformations, and sorption), it is now important 
to examine the linkages between these processes. Coupled-processes 
models provide the stimulus for a paradigm shift-from the reductionist 
approaches to the relational approaches-where an investigation of the 
inter-relations among the processes is considered even more important 
than the examination of individual processes themselves. (8) 



The primary objective of this dissertation research is to investigate soil- 
solute-microorganism interactions and their importance in contaminant 
persistence and transport in soil and aquifer materials. Reactions that are 
important in coupling sorption, biodegradation, and transport of quinoline will be 
investigated. From these results, the bioavailability of NHCs and thus, the 
success of bioremediation practices will be assessed. 

The following questions are proposed to address the following solute- 
sorbent-microorganism interactions: 

(1) Solute-sorbent What sorption processes limit bioavailability of 
NHCs in remediation practices? Is the nonequilibrium sorption of 
NHCs accurately described by the bicontinuum model? 

(2) Microorganism-sorbent-solute: Do bioremediation practices 
influence NHC sorption and transport? 

(3) Solute-microorganism: What essential nutrient and oxygen 
contents are required for biodegradation? 

(4) Microorganism-sorbent. Is bacterial activity (i.e., biodegradation) 
altered in the presence of surfaces? 



23 
The following chapters address the questions stated above by studying 

quinoline sorption and degradation. Quinoline, a NHC, is a contaminant found 
in energy-derived waste materials and products and has the potential to be 
transported to the subsurface soil and groundwater (Zachara et al., 1986). 
Quinoline sorption has been characterized in batch systems using clay minerals 
and soils. Desorption was recently shown to limit biodegradation of quinoline to 
its primary metabolite (2-hydroxyquinoline) in batch systems (Smith et al., 1992). 
In Chapter 2, process-level sorption kinetics of quinoline are examined and the 
utility of the bicontinuum model is evaluated. Understanding the behavior of 
quinoline sorption in flow through systems is necessary to determine the 
processes controlling bioavailability. Equilibrium and mass transfer coefficients 
for sorption and desorption were measured using batch and miscible 
displacement techniques. The bicontinuum sorption model coupled with the 
advective-dispersive solute transport model (during one-dimensional steady, 
water flow) was used to assess the behavior of NHCs. This information was 
then used to determine the rate-limiting processes controlling bioremediation 
practices of NHCs. 

The impact of biomass on the sorption and transport of three solutes 
(naphthalene, 45 Ca, quinoline) in a subsurface soil are investigated in Chapter 
3. These compounds were selected because of their known interactions in soil 
(i.e., cation exchange or hydrophobic partitioning). Miscible displacement 
techniques were used to measure sorption and transport of the above 



24 
compounds during steady, saturated water flow conditions through 

homogeneously packed, sterile or bacterial-inoculated soil columns. Pre- 

inoculation of the Norborne soil with bacteria (10 8 cfu/g) simulates 

contaminated subsurface soils and aquifers where bacterial populations may be 

high. In this chapter I investigated the consequences of biostimulation practices 

that attempt to remediate contaminated sites. 

In Chapter 4, I explored the process coupling of sorption and 
biodegradation of quinoline in flow through systems. First, growth limiting 
factors were determined using miscible displacement techniques. This was 
accomplished by monitoring breakthrough of quinoline and its primary 
metabolite, 2-hydroxyquinoline, in bacterial-inoculated columns. Second, a 
continually stirred, flow-through reactor was designed to monitor rapid 
biodegradation kinetics and to assess the impact of surfaces on 
biodegradation. These studies were used to determine processes important in 
coupling sorption and biodegradation by investigating the impact of surfaces on 
bacterial activity, and the conditions necessary for successfully remediating 
contaminated sites. 

Insights gained during my investigation of coupled processes and the 
arduous task of dealing with living organisms are summarized in Chapter 5. 
The significance, failures, and future opportunities of this research are also 
presented in this chapter. 



CHAPTER 2 

CHEMODYNAMICS OF N-HETEROCYCLIC COMPOUNDS IN ABIOTIC 

SYSTEMS: BATCH AND FLOW-THROUGH TECHNIQUES 



Introduction 

Sorption of NHCs may occur via cation exchange of the protonated 
species on clay minerals or in organic matter and/or via partitioning of the 
neutral species into organic matter. In contrast, sorption of HOCs occurs 
primarily via "partitioning" into the organic phase. The dynamics of HOC 
sorption have been conceptualized and described by the bicontinuum sorption 
model (Karickhoff, 1980; Brusseau et al. 1991, Ball and Roberts, 1991). 
However, the adequacy of this model to describe the behavior of NHCs is 
uncertain. 

Nonequilibrium sorption has been separated into transport- and sorption- 
related processes. Transport-related nonequilibrium affects both sorptive and 
nonsorptive compounds and results from heterogeneities in the flow paths. 
When using non-aggregated media in packed-column laboratory studies, 
transport-related nonequilibrium is generally determined to be negligible. 
Sorption-related nonequilibrium results from specific solute-sorbent interactions 
or diffusive mass transfer constraints. Organic matter is considered to be a 
flexible polymer-like substance (Behar and Vandenbroucke, 1987) in which 

25 



26 
diffusional constraints within the matrix (IOMD) cause sorption nonequilibrium of 

HOCs. Nonequilibrium may also result from IPD (intraparticle diffusion) inside 

microporous particles which contain organic coatings. HOCs are not likely to 

exhibit chemical nonequilibrium because sorption occurs via partitioning 

(Karickhoff et al., 1979; Chiou et al., 1983). Sorption of inorganic cations has 

been shown to be rapid onto cation exchange sites and limited only by diffusion 

to/from the exchanger surface (Nkedi-Kizza et al., 1989). Brusseau et al. 

(1991) suggested that compensation of charge (i.e, cation sorption) likely 

occurs near surfaces of organic matter; therefore, diffusional constraints of 

HOCs and cations differ because of the path length and sorbent matrix. 

Specific interactions of NHCs with the sorbent as well as and mass transfer 

constraints within organic matter or phyllosilicate minerals are likely to limit 

sorption of NHCs. Sorption of the quinolinium ion (i.e., cationic form of NHC) 

onto predominantly organic matter associated CEC sites was suggested to be 

faster than sorption of the neutral species (i.e., similar to HOCs) into the organic 

matrix (Brusseau et al., 1991). 

Quinoline, is a contaminant found in energy-derived waste materials and 

products. Therefore, it was selected as a probe to evaluate the bicontinuum 

sorption model and to further characterize the sorption dynamics of NHCs. A 

first-order model did not adequately describe the complex interaction of 

quinoline sorption onto clay modified alumina where 90% of the sites were 

suggested to be readily available (Figure 2-1; Szecsody and Streile, 1992). 



27 




150 
Pore Volumes 

ooocP 



200 



250 




300 



350 



150 200 250 
Pore Volumes 

Figure 2-1. Calcium (□) and quinoline (o) BTCs: a) pH 6, v = 0.162 cm/s and b) 
pH ■ 6.9, v = 0.063 cm/s. Lines correspond to equilibrium (solid) 
and first-order models (dash), (from Szecsody and Streile, 1992). 



28 
Therefore, the mechanisms influencing quinoline sorption must be accurately 

determined to assess the conceptual validity and adequacy of the bicontinuum 
model. 

Quinoline Sorption Dynamics 
Figure 2-2 describes the ionization of quinoline between the protonated 
(QH + ) and neutral species (Q) as a function of pH. Mathematically, the 
ionization of quinoline is represented by 

QH + ^ 0° + H + (2-1) 

* - I93lffl (2-2) 

[QH + ] 

where K a is the ionization constant. 

Sorption of quinoline has been characterized in batch systems using soil 
and clay materials (Ainsworth et al., 1987, Zachara et al., 1988; 1990), and in 
column studies using modified and pure clays (McBride et al., 1992; Szecsody 
and Streile, 1992). Quinoline sorption was adequately described by the 
Freundlich isotherm (see Chapter 1). These studies suggest that the 
quinolinium ion (QH + ) is the predominant species sorbed via cation exchange 
at low concentrations. As surface coverage increases, quinoline likely 
occupies lower energy sites and multiple layers of quinoline at the sorbent 
surface may form. More importantly, sorption varies with pH reflecting quinoline 
ionization (Fig. 2-2, eq 2-1) and preferential retention of the organic cation. 



29 



1.00 



0.75 



+ 



a 

.2 0.50 

6 

Li. 



0.25 - 








pK a =4.92 



4 6 8 

PH 



10 



Figure 2-2. Quinoline speciation diagram and the protonated and 
neutral species structures. 



30 
Sorption of the quinolinium ion has been shown even at pH values as much as 

2 units greater than its ionization constant (pK a = 4.92) (Zachara et al., 1986; 

Smith et al., 1992). Therefore, in a Ca +2 saturated homoionic soil, the following 

cation exchange reaction can be used to describe quinoline exchange with 

Ca +2 : 

CaR 2 + 2QH + ** 2QHR + Ca +2 (2-3) 

where QH + is the aqueous concentration of the quinolinium ion, Ca +2 is the 
aqueous concentration of Ca +2 CaR 2 is the Ca on the exchanger complex, and 
QHR is the quinoline on the exchanger complex. The equilibrium constant 
describing this reaction is given as follows: 

. [(QHR)> (Ca- 2 )] 
[(CaRJ(QH+) 2 ] 

where ( ) refers to the activity of QH + and Ca +2 in the solution and exchange 
phase. The conditional equilibrium constant (°K ex ) or Vanselow selectivity 
coefficient (KJ for eq 2-3 is depicted as 

K - [X ° HR {Ca+2)] (2-5) 

[WO"*) 2 ] 

where X is the mole fraction, (QH + ) is the activity of QH + in solution, and (Ca +2 ) 
is the activity of Ca +2 in solution. In eq 2-5, the activities in the exchanger 
phase are represented by X. The selectivity coefficient (KJ is related to the 
equilibrium constant (KJ, if the reaction is reversible, by the relationship: 



31 



K. - K» %£ (2 - 6) 

f QH + 



where the activity coefficients in the solid phase (f) of the exchanging ions 
convert activity to mole fraction. 

Quinoline and other NHCs form complexes with negatively charged solid 
surfaces such as clay layer silicates (Zachara et al., 1986; 1987; 1988). 
Selectivity coefficients (KJ were developed for comparing the affinity of one 
cation versus another to occupy a cation exchange site. The exchange of 
quinoline and Ca +2 does not solely consider cation exchange because of the 
strong quinoline-surface complexes. In this example, K v includes the exchange 
of quinoline and Ca +2 and the stability of the quinoline complexes on the 
exchange phase. In eq 2-5, K v > 1 indicates selectivity for QH + in the solid 
phase whereas K v < 1 indicates Ca +2 is preferred. The high quinolinium 
exchange selectivity coefficient on Na-montmorillonite (K v = 200 to 1300) and 
clay isolated from the Norborne soil (K v = 10 4 to 10 6 ) suggests that strong 
quinoline-surface complexes are formed (Ainsworth et al., 1987; Zachara et al., 
1990). In these soils and pure clay minerals, K v varied with pH and with 
surface coverage which was suggested to be due to sorption of the neutral 
species, occupation of high energy sites at low surface coverages, and surface 
condensation. Reconfiguration of the quinoline molecule to a planar position 
within interlayers of clay minerals may contribute to the hysteretic behavior 
(Zachara et al., 1986; 1990) implying constraints to quinoline desorption. The 



32 

implication of this on quinoline transport in soils and aquifers will be examined in 
a later section (Chapter 5). 

A high K v for quinoline suggests that quinoline may be favored over 
inorganic cations on the exchange complex. Other NHCs (e.g., acridine, 
pyridine), were shown to reduce quinoline sorption in low pH soils (4.7) where 
compounds are protonated and sorption occurs via cation exchange (Zachara 
et al., 1987). However, competition in soils where the neutral species 
predominates (pH 7) was not apparent. 

Predictive models have not been developed which adequately describe 
the sorption and transport of NHCs (Szecsody and Streile, 1992). Sorption of 
NHCs has been shown to be dependent upon the pH and cation exchange 
capacity of the sorbent matrix. Therefore, accounting for these factors with an 
individual parameter would enable the use of a predictive model for soils that 
vary in their cation exchange capacity and pH. If the predominant sorption 
mechanism is cation exchange, normalization of quinoline sorption to QH + and 
the CEC of the soil of may be described by 

S,=K tf C, 1/n (2-7) 

where S, is the sorbed concentration [mol QH + /mol (-)], K lf = Freundlich-type 
sorption coefficient [(L (1/n) mol QH +[1 - (1/n) Vmol c (-)], C, = equilibrium solution 
concentration [mol QH + /I_]. and 1/n = isotherm constant. This relationship 
resembles a Freundlich-type isotherm where the K tf describes the sorption of 
NHCs accounting for variations in the cation exchange capacity and pH of the 
soil. 



33 
The ion exchange of quinoline and Ca +2 in a system initially saturated 

with Ca +2 was described in eq 2-5 and represented by K v . Freundlich 

isotherms are not considered to be ion exchange isotherms. However, 

assuming sorption of the protonated species onto cation exchange sites and 

the fraction of the CEC occupied by quinoline is small, the K tf may be related to 

the K v by the following relationship: 



K* 



N 



N fot* 



K, (2-8) 

N 



where N is the normality of the background electrolyte solution. However, 
Zachara et al. (1988) predicted, based on eq 2-1, that the total sorbed quinoline 
exceeded the fraction of quinoline existing as the quinolinum ion. Additional 
sorption of quinoline could have been due to sorption of the neutral species, 
clustering of the sorbate, surface condensation, or protonation of quinoline at 
the exchanger surface (Ainsworth et al., 1987; Zachara et al., 1988). However, 
measurement of enhanced acidity, thus, protonation of quinolinium at soil 
surfaces, is not a trivial task. Sorption of the neutral species and cooperative 
adsorption have been reported (Ainsworth et al., 1987) to occur at high surface 
coverages via entropic or van der Waals forces. 

Sorption of quinoline onto soils (pH 4 to 7) was thought to occur via 
cation exchange in the presence of cosolvent mixtures [volume fraction of 
cosolvent (fj < 0.4] (Zachara et al., 1988). Fu and Luthy (1986a) suggested 
that cosolvents decreased quinoline sorption in response to an increase in 



34 
quinoline solubility. Quinoline isotherms at high concentrations (25 to 1000 

mg/L) were suggested to be linear in water-methanol systems up to f c = 0.5 

(Fu and Luthy, 1986b). Sorption at low concentrations (w 0.15 /xg/mL) was 

suggested to be nonlinear in aqueous systems (1/n = 0.75) and in 

methanol/water solutions (20 vol % methanol; 1/n = 0.67) (Zachara et al., 

1988). Isotherm linearity has been shown to increase upon addition of 

cosolvents for partitioning of solutes into an organic matrix; however, if ion 

exchange predominates specific interactions with cation exchange sites may be 

altered. For organic bases and acids, addition of solvents increases the fraction 

of neutral species (Perrin et al., 1981; Lee, 1993). In the presence of 

cosolvents, changes in the pK a values for organic bases are minimal (Perrin et 

al., 1981). However, substantial increases in pK a values for organic acids have 

been shown due to solute-solvent interactions resulting in decreased sorption of 

phenolic compounds and increased sorption of carboxylic acids (f c > 0.2) (Lee, 

1993). 

Considering that the quinolinium ion sorption occurs predominately onto 

cation exchange sites at low surface coverages, one could envision rate-limited 

desorption of quinoline out of interlamellar regions of clay minerals and 

aggregates or intra-organic matter regions. Such mass transfer constraints 

delay the release of contaminants leading to persistence, inadequate 

remediation, and limited bioavailability. 



35 
Research Question and Tasks 

The primary objective of these studies are to investigate the process-level 
kinetics of quinoline sorption by soils addressing the question: what are the 
rate-limiting processes controlling bioremediation practices of NHCs? 
Equilibrium and mass transfer coefficients for sorption and desorption were 
measured as a function of pH, molarity (M) and sorbent. The bicontinuum 
nonlinear sorption model coupled with the advective-dispersive solute transport 
model was used to assess quinoline sorption and transport during one- 
dimensional, steady water flow. 

Materials and Methods 
Sorbent 

The soils used in this study and their properties are presented in Table 2- 
1 . Soils were sterilized for 30 min by steam autoclaving 50 g samples that were 
brought to 15% water content and incubated for 24 hours. The process was 
repeated two additional times and the soil was used in all subsequent 
experiments unless otherwise noted. The soils used in the batch and column 
experiments were initially saturated with Ca +2 . Cation exchange measurements 
were measured at the pH of the soil (See Table 2-1). 

Solutes 

Pentafluorobenzoic acid (PFBA; 150 mg/L) and ^l 2 (6000 cpm/mL) 
were used as conservative, nonsorbing tracers to assess the hydrodynamic 



36 



Table 2-1. Soil properties before and after steam autoclaving. 



pH in 0.005 




CEC 


location of 


Soil M CaCI 2 


foe 


cmol(-)/kg 


CEC 


Eustis 5.3 


0.0039 


3.20 


organic matter and kaolinitic 


Sterile Eustis 5.4 


0.0032 


4.44 


clay minerals 


Norbome 6.4 


0.0015 


11.91 


smectite clay minerals and 


Sterile Norborne 6.4 


0.0015 


11.76 


organic matter 


Webster 6.9 


0.037 


47.9 


organic matter and 

smectite clay minerals 



dispersion and extent of physical nonequilibrium conditions prevailing during 
transport through the soil columns (Brusseau and Rao, 1989a). Quinoline 
concentrations in the influent solutions for the column studies ranged from 4 to 
10 mg/L 14 C-quinoline (Sigma) and spiked to obtain solutions at 10,000 
cpm/mL Batch studies were conducted for 2-Hydroxyquinoline (2-HQ) and 
quinoline over the concentration range of interest at either 1 to 10 and 1 to 5 
mass to volume ratios. Isotopic exchange of 4C Ca and 4 ^Ca (6,000 cpm/mL) 
was also investigated. Aqueous solutions of the chemicals were prepared in 
filter-sterilized (0.2 jam) 0.005 or 0.05 M CaCI ? Background matrix solutions 
(0.005, 0.05 M CaCy were filter sterilized (0.2 /im) to minimize biodegradation 
of organic solutes. 



Experimental Setup 

Batch techniques (Nkedi-Kizza et al., 1985) were used to assess 
sorption/desorption kinetics and equilibrium constants for quinoline in sterile 
systems. A stirred batch reactor was used to measure quinoline sorption 



37 
kinetics. The soil fraction < 50 nm was used in the stirred batch reactor to 

minimize separation of the soil suspension. The soil fraction (2 g) was added to 

150 mL 0.005 M CaClg. At various time intervals, the suspension was sampled 

and immediately separated through a 0.45 nm teflon filter. The filtrate (C) was 

analyzed to determine the quinoline concentration at various time intervals for 4 

days. Flow-through column techniques (Brusseau et al., 1990) were utilized to 

determine sorption rate coefficients for quinoline using sterile background matrix 

solutions. The sterile soil was packed into a Kontes glass column (5 cm long, 

2.5 cm i.d.). Bed supports on both ends of the column consisted of a teflon 

diffusion mesh with a glass membrane porous filter (1 /xm). The pumps and 

tubing were disinfected by rinsing with methanol. The glass columns and 

solution vessels were sterilized by autoclaving. After packing, approximately 

150 pore volumes of 0.005 or 0.05 M CaCI 2 solution were pumped through the 

column to achieve saturated, steady water flow conditions. Experiments were 

conducted under saturated, steady water flow conditions at pore water 

velocities of 15 to 90 cm/hr. In displacement studies, the molarity (0.005 M, 

0.05 M) and pH of the displacing solution were varied. 

Solute concentrations were monitored continuously or by collecting 

column effluent fractions. Flow through UV detection (Gilson Holochrome or 

Milton Roy LDC) was monitored continuously at 230 nm for quinoline and 2-HQ 

and 254 nm for PFBA. Detector response was recorded using a strip chart 

recorder (Fisher Series 5000). Effluent samples were collected intermittently 



38 
and analyzed by HPLC-UV techniques (Gilson 115 UV detector, Gilson Model 

302 pump, Waters WISP 71 OB autosampler, HP333492A Integrator) to verify 

sample purity and to compare the initial solute concentration to the maximum 

effluent concentration. Quinoline and 2-HQ were eluted from a reversed-phase 

column (Supelco LCPAH column) at a flow rate of 1 mL/min with a mobile 

phase of 10/10/80 (v/v/v) methanol, acetonitrile and water adjusted to pH 2 

with HCI. Soil column effluent pH was monitored on-line using an Ingold 

microelectrode (Lee et al., 1991). Effluent fractions of the radiolabeled 

compounds were collected with an automatic sample collector (ISCO Model 

273). The activity of each radiolabeled compound was assayed using a liquid 

scintillation counter (Searle Delta 300). 

Data Analysis 

Retardation factors (R) were calculated from area above the BTC for 
quinoline and naphthalene (Nkedi-Kizza et al., 1987); a linear extrapolation 
technique was used to extend the BTCs to C/C =1 in order to estimate the 
area above the BTC. For 4J Ca pulses, the R was calculated by moment 
analysis techniques (Brusseau et al., 1990). The curve fitting program CFITIM 
(van Genuchten, 1981), which is based on nonlinear least-squares optimization 
techniques, was used to estimate the Peclet number (P) from the BTC for 
PFBA. For nonsorbed solutes (R = 1), two model parameters can be optimized: 
P and the solute pulse size (J). Since the pulse size was determined 
experimentally, only the value for P was estimated by fitting to the measured 



39 
BTC for PFBA or \\p. For sorbed solutes (R>1), five model parameters can 

be optimized: P,R, p, w, and J. For 4J Ca and naphthalene BTCs, R was fixed 

(estimated as described above), J was experimentally determined, P was fixed 

as the value estimated from PFBA BTCs, and the values of nonequilibrium 

sorption parameters {p and o) were estimated from parameter optimization 

using the CFITIM program. For quinoline BTCs, the curve fitting program 

FLOINT (Brusseau et al., 1989) with nonlinear sorption isotherms was used to 

estimate the parameters when flow interruption techniques were used to 

enhance the investigation of sorption nonequilibrium processes. 

Results and Discussion 
Sterilization Techniques 

Initial batch studies were conducted to characterize the sorption of 
quinoline and to assess techniques used for soil sterilization. Batch sorption 
experiments were conducted using three nonsterilized air-dry soils and two soils 
sterilized by steam autoclaving techniques. Autoclaving had minimal effect 
(<2%) on the properties of the Norborne soil (Table 2-1). CEC measured by 
4! Ca isotopic exchange (Babcock and Schulz, 1970) and the Mg NO 3 extract 
procedure (Rhue and Reve, 1990) resulted in similar values for nonsterilized and 
autoclaved soils (See Table 2-1). Measurement of 4J Ca isotopic exchange over 
time suggested that cation exchange on Norborne soil was completed within 
the first 5 minutes. Isotopic exchange, thus, migration of 4E Ca into the interlayer 
exchange sites, was virtually instantaneous. The CEC of the Eustis soil 



40 
increased about 28% after autoclaving. The standard deviation of the CEC 

estimates for this sample, however, was high. Nonuniformity in soil sampling 

may have caused some of this error. On the other hand, the increase may 

have been caused by release of organic acids, alteration of the organic matter 

structure, or a change in the interfacial pH though the bulk pH is the same. 

The soils (Table 2-1) varied in pH, cation exchange capacity, and location 
of charge. The quinoline sorption isotherm, plotted on a log-log scale, was 
normalized to the protonated species (QH + ) in the sorbed and solution phases 
and the CEC of the soil (mmol(-)/g). The sorption data for all soils can be 
represented by a single scaled isotherm (Figure 2-3), suggesting that quinoline 
sorption occurs primarily via cation exchange. Sorption isotherms were 
nonlinear (1/n = 0.68 to 0.8) over the concentration range investigated. At 
higher concentrations (Figure 2-3), sorption of quinoline increases in the 
Norborne and Webster soil. The S-type sorptive behavior for these soils occurs 
at high concentrations (100 mg/L), where > 95% of quinoline is present as the 
neutral species. 

Cooperative interactions between the sorbed species and multilayer 
sorption has been suggested to enhance quinoline sorption clay minerals at 
high concentrations (Ainsworth et al., 1987). However, at this concentration 
less than 1% of the cation exchange sites are occupied by quinoline. This 
behavior may result from aggregation of sorption sites where quinoline sorption 
occurs in collocation with clay mineral aggregates or organic matter. The 



41 



^ -3 



o 
£ 



© 
£ 



-4 



£_ -5 

o 

J -6 



-7 



• Eustis 

O Sterile Eustis 

* Webster 
■ Norborne 

□ Sterile Norborne 



□ 






W 



* 



^5 



* 



# 



,D 



#T 



EED 



-9 



-8 



-7 



-6 



-4 



Log C, [mol QH /L] 



Figure 2-3. Quinoline sorption isotherms for three soils normalized 
to their cation exchange capacity and to the fraction of 
protonated species (See eq 2-7). 



42 
Eustis soil (pH 5.3) has a higher fraction of QH + present for the same initial 

quinoline loading than the other soils (pH 6.4 and 6.9) (see Figure 2-2). The 

isotherm nonlinearity for the Eustis soil remains constant at high concentrations 

of QH + . This suggests that sorption of the neutral species may be occurring in 

the higher pH soils. Another possible explanation is that high energy cation 

exchange sites are the first sites occupied by quinoline, followed by sorption 

onto lower energy sites such has been shown for sorption of inorganic 

compounds (O'Connor et al., 1983). 

Investigation of quinoline sorption kinetics suggested that sorption 
occurred via a three step process (Figure 2-4). About 20% of quinoline sorption 
occurred onto readily available or instantaneously accessible sorption sites. 
These sites have typically been thought to exist on external regions of the 
sorbent matrix (Brusseau and Rao, 1990). However, these sites may include 
external sites or readily accessible internal sites depending upon the 
architecture of the sorbent (Okuda, 1993). Sorption of quinoline occurs 
predominantly on cation exchange sites located within organic matter and 
smectite minerals. The slower rates of quinoline sorption likely correspond to 
sorption and redistribution in the internal less-accessible regions of the sorbent. 

In a binary solute batch system, quinoline sorption at low concentrations 
was unaffected by the presence of its primary degradative metabolite, 2- 
hydroxyquinoline (2-HQ), at pH 6.8 (Figure 2-5). The data points at the highest 
quinoline concentration had the greatest amount of scatter in the data which 




-0.1 - 



-0.2 



Quinoline 10 M 
Soil < 50jUm 



o 
U-0.3 
o 



-0.4 



-0.5 



-0.6 







10 20 30 40 

Time (hr) 



50 



60 



Figure 2-4. 



Stirred batch reactor (a) and quinoline sorption onto 
the Norborne soil fraction < 50 jum (b) (where C = 
quinoline filtrate concentration and C = the initial 
quinoline concentration). 



44 



/ u 


. 2HQ (mg/L) 


** 


60 


o o 

D 1 
A 5 


Rd 


50 


* 10 


o 
o 


240 

0) 

-30 
(0 




20 


© 




^0 
n 


■ O 

& , 1 


I.I. 



8 
C (mg/L) 



12 



16 



Figure 2-5. Sorption of quinoline on the Norborne soil in the 
presence of 2-hydroxyquinoline. 



45 
caused variation in the 1/n values. McBride et al. (1992) suggested that by 

adding 2-HQ (5 and 20 mg/L) quinoline sorption in soil columns was reduced 

as much as 23%. Competitive adsorption has been shown for NHCs such as 

pyridine, quinoline, and acridine (Zachara et al., 1987) where the compounds 

adsorb onto the same limited number of cation exchange sites. For HOCs, 

competitive sorption is not likely because sorption occurs via partitioning (Chiou 

et al., 1983). 2-HQ exists in its neutral form (pK a = 1.7) in the Norborne soil. 

The predominant mechanism of 2-HQ sorption is hydrophobic partitioning, while 

quinoline sorption occurs predominantly onto cation exchange sites. Therefore, 

competitive sorption was not expected. If however, organic matter is located in 

conjunction with the phyllosilicate minerals (Stevenson, 1985) quinoline sorption 

may have been reduced due to the interference of 2-HQ and quinoline sorbing 

in the same location of the organic matter-mineral complex. This behavior may 

become more apparent in column studies (McBride et al., 1992) where 

diffusional mass transfer constraints further limit sorption. These studies 

suggest that 2-HQ production upon quinoline biodegradation is not likely to 

reduce quinoline sorption by competing for available sorption sites. 

Sorption Dynamics 

Physical characterization . The 3 H 2 and PFBA breakthrough curves 
(BTCs) for all soil columns were symmetrical and sigmoidal in shape (e.g., 
Figure 2-6) suggesting the absence of transport-related nonequilibrium. Peclet 
numbers (P) were all greater than 80 indicating minimal hydrodynamic 



46 



O 



0.8 



o 

« 0.6 

i— 
#-■ 

c 
© 
o 

o 0.4 
O 

m 
> 

« 0.2 
o 



r- 



e- 



■e- 



o 
o 



o 
o 

o< 

o 



Oi 

o 



4U O 

Pore Volumes (p) 



o 



o 



:o, 



o 
• 


• 3 H 2 


o 


O PFBA 


o 
• 




o 




o. 





Figure 2-6. Examples of breakthrough curves for PFBA and H 2 
in Norborne soil columns. 



47 
dispersion (Table 2-2). Slight retardation (R « 1.15) of BTCs for 3 H 2 on the 

Norbome soil suggests that this tracer was sorbed. Sorption of 3 H 2 onto a 

soil high in iron oxide content that contains predominately kaolinitic clay 

minerals has been previously reported (Nkedi-Kizza et al., 1982). The Norborne 

soil also contains iron oxides with 2:1 type clay minerals (Zachara et al., 1990); 

thus, 3 H 2 sorption is likely. Sorption of 3 H 2 may indicate that water is 

exchanged with hydrated sorbed ions on the clay surface (Szecsody and 

Streile, 1992). Batch studies were conducted to measure 3 H 2 sorption onto 

sterile Norborne soil. The sorption coefficient (K d ) was 0.03 (± 0.001) mL/g. 

These K d values are consistent with retardation factor (R) values ranging from 

1.09 to 1.12 observed in different columns. The pore volumes determined by 

H 2 after correcting for sorption resulted in similar pore volumes as 

determined using gravimetric methods, and the BTC data for displacement. 

3 H 2 was not sorbed onto the Eustis soil (R » 1.0). 

Chemical characterization. Monitoring 45 Ca and quinoline sorption and 
transport under specific chemical and physical conditions (e.g., molarity of 
solution, pH, and pore-water velocity) will help understand mechanisms 
influencing quinoline behavior. The data for 45 Ca and quinoline were utilized to 
explore the accessibility of cation exchange sites by an inorganic cation and an 
organic cation. Nonequilibrium sorption was explored by observing isotopic 
exchange of both 45 Ca/ 40 Ca and 14 C-quinoline/ 12 C-quinoline, as well as the 
exchange of quinoline for calcium. The behavior of these two solutes were 



48 



Table 2-2. Column parameters for sterile soil columns. 






CaCI 2 


pH 


9 


e 


P 


Column ID mol/L 


g/cm 3 


mL/cm 3 


Norborne soil columns: 










BQ5 0.005 


7.0 


1.48 


0.44 


80 


A 0.005 


7.0 


1.49 


0.45 


137 


B 0.05 


6.2 


1.54 


0.42 


108 


BQ3 0.005 


6.8 


1.48 


0.44 


190 


BQ8 0.005 


6.2 


1.47 


0.49 


nd* 


BQ10 0.005 


3.0 


1.45 


0.45 


nd 


Floint 0.05 


6.2 


1.42 


0.44 


120 


pH5.1 0.005 


5.1 


1.47 


0.44 


97 


pH4.7 0.05 


4.7 


1.51 


0.47 


nd 


Eustis soil columns: 










BQ2 0.005 


5.3 


1.79 


0.32 


110 


DCMA 0.005 


5.3 


1.75 


0.33 


84 



* nd = not determined 

compared in a soil where sorption occurred primarily in organic matter (70%) 
and kaolinitic minerals, and in a soil where sorption occurred primarily on 
smectite type minerals and organic matter. 

Figure 2-7 shows the BTC for 45 Ca in 0.005 and 0.05 M CaCI 2 . The 
retardation factor for 45 Ca in the 0.005 M CaCI 2 soil column is 37.6, whereas 
the R in 0.05 M CaCI 2 is 5.0. The sorption coefficient (K d ) of 45 Ca is related 
directly to the CEC of the soil, and inversely to the normality (N) of the 
background electrolyte solution (K d » CEC/N) (Wilklander, 1964). Therefore, a 
factor-of-ten increase in N should result in a 10-fold decrease in K d . This was 
indeed the case for sorption coefficients for 45 Ca in the sterile 0.005 M CaCL 



49 



p u □ • 



3> 0.8 

\. 

O 

>— ' 

c 
o 

% 0.6 


O 

C 

© 

© 
> 

J2 

© 

0£ 



0.4 



0.2 




19.2h 



17.8h 



Flow Interruption 



n 



o 



□ 



n 



0t& 



^£ 



oQuinoline pH 6.2 


• Quinoline pH 7 


n 45 Ca 


■ 45 Ca 



10 



20 30 40 

Pore Volumes (p) 



50 



60 



Figure 2-7. Quinoline and 45 Ca breakthrough curves with flow 
interruptions in 0.005 M (closed symbols) and 0.05 M 
(open symbols) CaCI 2 Norborne soil columns. 



50 
column (1.0 mL/g) and 0.05 M CaCI 2 column (11.0 mL/g). In contrast, ionic 

concentration (molarity) of background matrix had minimal impact on quinoline 

sorption at pH > 6.2 (Figure 2-7). The pH of the 0.005 M CaCI 2 column is 7 

and the pH of the 0.05 M CaCI 2 column is 6.2. The fraction of protonated 

species is greater at pH 6.2 (5%) versus pH 7 (1%). The decrease in pH in the 

lower background matrix concentration (0.005 M) column may compensate for 

the decrease in sorption due to higher ionic concentration. Batch studies at pH 

6.2 for 0.05 M CaCI 2 and in pH 6.8 for 0.005 M CaCI 2 suggest that sorption 

(K d ) is greater («11%) as the molarity of the background matrix solution 

decreases. Charge compensation in the diffuse double layer at higher 

electrolyte concentrations may reduce the sorption of quinoline. In a subsoil 

with a pH 7, the effects of ionic strength on quinoline sorption were negligible 

(Zachara et al., 1986). 

The influence of pH is evident upon comparing the BTCs in Figure 2-7 

and 2-8 at the same background electrolyte concentrations. A decrease in pH 

results in a increase in quinoline sorption. Increased sorption at lower pH 

values is expected based on the increase in the fraction of QH + . The influence 

of background electrolyte concentration was not clearly determined. Previous 

investigation suggested that sorption decreased 60% at pH values near its pK g 

when the ionic strength increased from 0.001 to 0.1 M CaCI 2 (Helmy et al., 

1983; Zachara et al., 1986). 



51 



0" 

v. 

O 



0.8 



© 

£ 0.6 

c 
© 
o 

o 0.4 
O 

© 
> 

w 0.2 
© 



«>©. 




Flow 



X 



Interruption 



8.8 h 



16.6d 



o pH 4.6; R = 28.6 
• pH 3.0; R= 138 



100 



150 



200 



250 



Pore Volumes (p) 



Figure 2-8. Quinoline breakthrough curves in 0.005 M (closed 
symbols) and 0.05 M CaCI 2 (open symbols) in pH 
adjusted Norborne soil columns. 



52 
Measuring the influence of background electrolyte concentration on 

quinoline was confounded by a simultaneous change in electrolyte 
concentration and pH (Figure 2-7). Poising the soil pH at some value other 
than the natural pH is often difficult. Repeated flushing of the soil column with 
0.005 M CaCI 2 resulted in a pH « 6.9. The final pH after flushing the soil 
column with 0.05 M CaCI 2 ranged from 6.2 to 6.4, decreasing the pH about 0.6 
pH units. As the pH of the soil approaches the pK a of the compound of 
interest, sorption is increasingly sensitive to slight pH changes (Figure 2-2). 
Therefore, sorption measurements of ionizable compounds must be conducted 
at a constant pH. 

The use of nutrient solutions was shown to alter the sorption of quinoline 
(McBride et al., 1992). As a result, use of buffers was avoided. To alter the soil 
pH, HCI may be added to the system. The addition of other ions may change 
the overall ionic strength and the cation exchange complex, thereby influencing 
quinoline sorption and possibly the phyllosilicate mineral structure. A titration 
device was used to maintain a constant pH of soil-suspensions while quinoline 
sorption was measured (Zachara et al., 1990). However, this procedure does 
not lend itself to use in flow-through column techniques. In these column 
experiments at the lower pH values, the background electrolyte solution was 
adjusted with HCI and flushed until the pH was essentially constant (± 0.3 pH 
units). Soil columns were flushed at 0.5 mL/min for about 2 weeks. Additional 
acid was not added to adjust the pH of the quinoline solution due to changes in 



53 
electrolyte concentrations and ionic composition. Therefore, the pH was not 

adequately controlled. Experimental techniques must be carried out with the 

utmost detail when investigating the behavior of ionizable compounds. A 

controlled experiment with the system poised at a particular pH value has not 

been conducted to accurately measure the influence of ionic strength on 

quinoline sorption in soil columns. 

Flow interruption. The accessibility of the cation exchange sites (i.e, clay 
interlayer positions and organic matter) was evaluated by examining the 
dynamics of 40 Ca/ 45 Ca isotopic exchange and exchange of quinoline for 40 Ca. 
The 45 Ca BTC was symmetrical and showed about a 5% drop in concentration 
after an 18-hour flow interruption in the 0.005 and 0.05 M CaCI 2 columns 
(Figure 2-7). This suggests that cation exchange and diffusion into clay 
interlayer sites and organic matter regions was rapid, and that near equilibrium 
conditions were attained under flow conditions for the column. Flow 
interruptions suggested that migration of 45 Ca into interlayer sites and organic 
matter matrices was not limiting mass transfer or isotopic exchange kinetics. 
Szecsody and Streile (1992) also found isotopic exchange of 40 Ca/ 45 Ca to be 
rapid in columns packed with clay-modified alumina. Exchange of 40 Ca/ 45 Ca in 
organic matter was rapid and not limited by mass transfer into the organic 
matrix (Nkedi Kizza et a!., 1989). They speculated that the compensation of 
charge may occur at the exterior of the organic matter matrix and Ca does not 
necessarily need to migrate within the sorbent. 



54 
Considerable asymmetry of the quinoline BTC at » pH 7 in the sterile 

Norborne soil (0.05 and 0.005 M CaCI 2 ) is indicative of nonequilibrium behavior 

during displacement of quinoline for ^Ca (Figure 2-7). A large drop in effluent 

concentration («35 to 50%) during the flow interruptions greater than 17 hours 

indicates strong nonequilibrium behavior (Brusseau et al., 1989). Figure 2-9 

shows the nonequilibrium behavior upon repeated flow interruptions in the 0.05 

M CaCI 2 Norborne soil column at pH 6.2. The first flow interruption (at 20 

hours) results in a 50% drop in concentration. Subsequent flow interruptions 

(24 hours) suggested that quinoline sorption is rate-limited into interlayer 

positions of phyllosilicate minerals and possibly into interior regions of organic 

matter matrices. 

Symmetrical BTCs for PFBA and 3 H 2 preclude physical nonequilibrium 
constraints (e.g., mobile-immobile water) as a possible reason, and 45 Ca cation 
exchange was rapid. Therefore, quinoline sorption nonequilibrium must be due 
to other constraints. 

O'Loughlin et al. (1991) reported that sorption of a N-heterocyclic 
compound (2-methyl pyridine) into 2:1 clay interlayers was rate-limited, whereas 
sorption onto edge-sites of kaolinite was rapid which suggests that steric 
hindrances are limiting sorption. However, similar molecular dimensions of 
quinoline (1.02 nm X 0.76 nm x 0.36 nm; Weast, 1984) and hydrated Ca (0.6 
nm; Bohn et al., 1979) suggest that size considerations alone are not likely to 
account for the observed sorption nonequilibrium of quinoline. Szecsody and 



55 



E 
O 

w 0.6 



© 
o 

o 0.4 
O 

@ 
> 

2 0.2 
cc 



% 




c 



° 

00' 



o 



Quinoline 
Model fit 



10 20 30 

Pore Volumes (p) 



40 



Figure 2-9. Repeated flow interruptions for quinoline in a 0.05 M 
CaCI 2 (pH 6.2) Norborne soil column and bicontinuum 
model fit. 



56 
Streile (1992) attributed sorption nonequilibrium to kinetic constraints from site- 
specific chemical processes between the quinoline and montmorillonite. Over 
the concentration range used in this study, the protonated form is likely the 
predominate species sorbed via cation exchange. In the bulk solution of the 
soil columns, quinoline exists essentially in the neutral form. Zachara et al. 
(1990) demonstrated that even when pH values are pH « (pK + 2) and most of 
quinoline exists in its neutral form, the quinolinium ion is still the predominant 
form sorbed. In addition, surfaces can be up to 2 units lower in pH than the 
bulk solution pH (Bates, 1973) and protonation reactions are rapid. Therefore, 
availability of quinolinium ions in solutions is not likely to limit sorption. 

The bicontinuum model provided an inadequate description of quinoline 
behavior in Norbome soil columns (Figure 2-8, 2-9). The frontal portion of the 
curve adequately describes the rapid access to the easily accessible external 
sites. Nonlinearity of the quinoline sorption also caused self sharpening of the 
front of the BTC. The model fits were optimized for nonequilibrium parameters 
6 and o (Table 2-3), and are shown in Figure 2-9. The quinoline displacement 
in the column adjusted to pH 4.7 was conducted at 0.5 mL/min, whereas 
displacement studies in the other three columns listed in the Table 2-3 were 
conducted at « 2 mL/min. The Norborne soil has 0.16% organic matter in 
addition to smectite clay minerals. The large fraction (0.5) of sites 
instantaneously accessed by quinoline was attributed to sorption on edge sites 
(as much as 20%) and easily accessible interlamellar sites of smectite minerals 



57 



Table 2-3. Summary of estimated transport parameters for quinoline. 



ID pH R Kf o 6 F k 2 



BQ5 7.0 11.0 3.18 0.762(0.52-1.0) 0.536(0.47-0.59) 0.493 1336 

Floint 6.2 12.6 3.87 0.814(0.41-1.22) 0.508(0.43-0.59) 0.466 1337 

pH4 4.7 28.6 8.58 0.178(0.17-0.18) 0.821(0.79-0.85) 0.814 074 

BQ10 3.0 140 43.1 0.261(0.11-0.41) 0.503(0.26-0.75) 0.499 041 

BQ2 4.75 0.69 1.727(0.98-2.47) 0.507(0.41-0.60) 0.375 8 286 

DCMA 5.3 11.0 1.82 0.984 (0.39-1.58)) 0.535 (0.42-0.65) 0.488 2 615 



* values in parenthesis are 95% confidence intervals. 

and exterior regions of organic matter. Simultaneously describing the large 
fraction of instantaneously accessible sites and the slow redistribution of 
quinoline within the clay interlayers is not possible using the bicontinuum model. 
Therefore, rapid sorption of the quinolinium ion followed by the rate-limited 
diffusion of quinoline into the phyllosilicate minerals is not an accurate 
conceptualization for quinoline sorption. 

Specific chemical interactions (e.g., hysteresis, reconfiguration of the 
molecular arrangement) likely limit desorption, and steric hindrances may limit 
redistribution within phyllosilicate minerals. The molecular configuration was 
suggested to change from an upright position to a planar position within clay 
minerals (Zachara et al., 1988). As a result, desorption is strongly inhibited due 
to delocalization of charge over the entire molecular surface. Subsequent 
migration within interlamellar regions may be restricted due to desorption and 



58 
redistribution of the quinoline molecule and limited accessibility due steric to 

hindrances. 

The significance of the interlayer spacing in this smectite clay mineral 
during quinoline sorption is apparent, given that the majority (up to 80%) of the 
charge associated with the clay mineral originates in the interlayer spacing from 
isomorphic substitution. The predominant form of clay in the Norbome soil is 
biedellite which is characterized by substitution of Al +3 for Si +4 in the 
tetrahedral layer. The clay fraction was isolated from the Norborne soil and 
prepared for X-ray diffraction to measure changes in d-spacing upon 
replacement of quinoline for 40 Ca. Mounts were prepared by placing a known 
amount of clay suspension onto a clay tile and saturating with 1 M CaCI 2 . The 
sample was rinsed with deionized water to remove excess Ca. The tile was 
equilibrated for about 48 hours at both 56 and 87 % relative humidity and the d- 
spacing was measured. Sufficient quinoline was then added to the clay tile to 
occupy 1% of the total sites. Measurements of the d-spacing were repeated at 
56 and 87 % relative humidity. A decrease in the d-spacing upon addition of 
quinoline would indicate the collapse of the clay interlayers and a potential 
source of nonequilibrium sorption. 

No obvious changes in d-spacing were indicated in the 1% quinoline 
saturated samples compared to the Ca saturated samples at either relative 
humidity. A decrease in the d-spacing was detected upon decreasing the 
relative humidity. The d spacing was 1 .6 nm at 87% relative humidity of which 



59 
0.92 nm is occupied by an octahedral and tetrahedral layer. Therefore, the 

interlamellar region is approximately 0.68 nm. This procedure was limited by 

the fact that only 1 % of the total CEC sites were occupied by quinoline; 99% of 

the exchange sites were occupied by Ca. Therefore, no changes were 

detected. To enable the detection of d spacing changes a larger fraction of 

sites would need to be saturated with quinoline. However, saturating the 

exchange complex with quinoline would likely alter the sorption mechanism and 

would not be comparable to low quinoline concentrations (see Figure 2-3). 

Figure 2-10 conceptualizes the process hypothesized for quinoline 

sorption onto smectite clay minerals. The size of the interlayer spacing of the 

smectite clay, the Ca, and quinoline are approximately drawn to scale. 

Quinoline replaces Ca on edge and readily accessible interlayer CEC sites 

(Figure 2-1 0a), representing the fraction of instantaneous sites (F) associated 

with the clay minerals. After this initial step, quinoline must desorb and migrate 

further within the interlamellar region of the clay mineral. Displacement of Ca 

by quinoline in interlayer regions may be physically constrained (Figure 2-1 0a), 

which may contribute to sorption nonequilibrium. Ca is hydrated and initially 

occupies CEC sites in the interlayer positions. Smith et al. (1992) suggested 

that quinoline displaced interstitial water upon reorientation to a planar position 

on the surface. Therefore, the hydration energies associated with quinoline and 

Ca may be important in understanding rate-limitations of quinoline sorption. 



1.6 



0.68 



nm 




Ca 




(£© 



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H 




^^m 



Sorption onto readily accessible sites 



60 





b 


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^^^W f§p 


Reorientation of quinoline to planar position 






H 

ayers 


d 


x^^m 




W^w 


Jim 


Collapse of clay inter! 



Figure 2-10. Conceptual diagram of quinoline sorption onto smectite clay minerals. 



61 
Quinoline may also be drawn into a planar orientation (Figure 2-1 Ob) 

delocalizing the charge over the whole quinoline molecule. At this stage, 

quinoline molecules in the solution phase may pass further into the interlamellar 

regions of the clay mineral due to compensation of the electrostatic charge by 

the previously sorbed quinoline molecule (Figure 2-1 Oc). Some of these sites 

may essentially be inaccessible once quinoline has occupied the interior of clay 

minerals and formed a stable surface complex. After breakthrough and 

washout of quinoline from the Norborne soil columns, mass balance suggested 

that 5 to 10 % of the quinoline introduced into the column remained on the soil. 

Repeated washing with 80% methanol was insufficient to completely wash out 

residual quinoline within the interior clay aggregates. Introduction of a cation 

more selective for the exchange complex than quinoline would be a more 

efficient method for removing quinoline from the exchange complex. 

The inability to successfully remove residual quinoline from interlayer 

positions further supports that strong quinoline surface complexes are formed 

or that the interlayers have collapsed (Figure 2-1 Od). This depicts the 

tetrahedral layer charge being drawn to the quinoline molecule and collapse the 

interlayer spacing restricting further migration into this region. Electrical 

neutrality must be maintained at all times suggesting that two quinoline 

molecules must replace one calcium. Therefore, the total collapse of the 

interlayer regions is not likely. However, formation of strong surface complexes 

and several molecules sorbed in the interlayers may create a buildup of 

molecules redistributed throughout the interlamellar region. 



62 

Isotopic exchange of 12 C-quinoline/ 14 C-quinoline was measured to 

determine the exchange of quinoline molecules during displacement with 0.05 M 
CaCI 2 in a Norborne soil column (Figure 2-11). The breakthrough of quinoline 
was first monitored in a 0.05 M CaCI 2 background matrix solution. After 7 flow 
interruptions (3 shown in Figure 2-9), the equilibrium solution concentration was 
98% of the influent concentration. At this point, a solution of 14 C-quinoline and 

C-quinoline (same total concentration) in 0.05 M CaCI 2 was introduced into 
the column. The breakthrough of 14 C-quinoline was delayed following 
preconditioning with 12 C-quinoline and the drop in relative concentration (25% 
versus 50%) during flow interruption decreased. Apparent increased retention 
(delayed breakthrough) in the 14 C-quinoline column may have been caused by 
decreased pH (6.1). However, the change in pH causes about a 1% increase 
in the fraction of QH + and it is not likely to cause this shift in breakthrough. 
Two cases will be presented as alternatives for the isotopic exchange data. 
First, the decreased drop in relative concentration of the 14 C-quinoline versus 
12 C-quinoline BTC suggests that equilibrium is more readily approached by 14 C- 
quinoline. A decrease in rate-limited sorption sites would result in a reduced 
drop during the flow interruption. This may occur if quinoline surface 
complexes are formed in interlamellar regions. However, this would 
simultaneously decrease cation exchange capacity, resulting in early quinoline 
breakthrough (lower R). In fact breakthrough was delayed, therefore, this was 
reasoned not to be a viable option. 



63 



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• C-Quinoline 








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10 20 


30 4i 








Pore Volumes 


(p) 





Figure 2-1 1 . Isotopic exchange of 12 C-quinoline and 14 C-quinoline 
in 0.05 M CaCI 2 (pH 6.2) in the Norborne soil. 



64 
Another possibility is that the 14 C-quinoline approaches equilibrium more 

rapidly than the 12 C-quinoline. The sigmoidal shape of the BTC for 14 C- 

quinoline is indicative of equilibrium sorption and a linear isotherm is expected 

from exchange of 12 C- and 14 C-quinoline. Quinoline sorption isotherms were 

nonlinear 1/n«0.7 in batch systems upon exchange of quinoline for ^Ca. The 

self-sharpening front for the 12 C-quinoline BTC is indicative of nonlinear sorption 

(Brusseau and Rao, 1989b). The sharp front may also indicate nonequilibrium 

conditions suggesting access into the interlayer positions and replacement of 

calcium is difficult. Initial access of quinoline into interlayer positions may 

enhance subsequent access of interlayer regions due to charge compensation 

and reorientation (Figure 2-1 Oc). To test this hypothesis, a BTC of 14 C- 

quinoline on the backside tail (5-10% residual quinoline) could be conducted. If 

the sharp front occurred on the BTC then it would suggest that as the percent 

of quinoline on the exchange complex increased access to other interlayer sites 

would increase. 

From these two cases, nonequilibrium conditions prevail upon 
introduction of quinoline, suggesting that some sites are extremely constrained 
by diffusional and chemical factors. A fraction of the sites are considered to be 
unavailable and thus, bioavailability is likely to be limited. 

In the pH 3 and pH 4.6 columns, the minimal drop in effluent 
concentration during flow interruption (Fig. 2-6) suggested that quinoline 
sorption is near equilibrium. However, the relative concentration only reaches 



65 
95-98% after the flow interruption. In the pH 6.2 column, C/C approached 1 

rapidly after the flow interruption. In the pH 6.2, 4.7, and 3 columns, the flow 
interruption resulted in a 50, 18, and 2% drop in relative concentration, 
respectively. Diffusion into clay interlayer positions is pH dependent. At first 
glance it appears that nonequilibrium is greater at higher pH values. However, 
as the pH decreases the fraction of protonated species increases and R 
increases which may alter access into these regions. A larger R, a highly 
selective exchange coefficient, and steric hindrances may further limit quinoline 
entry into the clay interlayer positions. Rate-limited sorption of quinoline may be 
related to both the magnitude of selectivity coefficients (Ainsworth et al., 1987) 
and the ability of quinoline to delocalize its charge over the entire surface of the 
compound (Zachara et al., 1990). 

Replacement of hydrogen ions for 40 Ca on exchange sites may alter the 
clay interlayer environment, thus, quinoline migration into interlayers. As a 
result, the ability to access interlayer positions as the pH decreases may be 
further constrained. It may be possible that mass transfer is restricted beyond 
the time allowed for flow interruption (8.8 h, pH 3 column), modeling the data 
assuming flow interruption occurred for a longer period of time (16.6 d) would 
result in a large drop during flow interruption. The model fit (granted the error 
associated with the use of this model) suggests that mass transfer is more 
constrained than indicated for the 8.8 hour flow interruption. However, a flow 
interruption for as much as 10 days in a pH 5 column resulted in only an 8% 



66 
drop in the relative concentration and approached a relative concentration of 

98%. The k 2 values determined from model fits for the lower pH columns are 

less than the higher pH columns (Table 2-3). Sorption is about 25 times faster 

at higher pH values than in lower pH soils. The trend indicates reduced access 

to interlayer positions as pH decreases. 

Consideration must be given to differences in the nature of organic 
matter versus clay minerals in describing the quinoline sorption. Diffusion of 
quinoline into interlamellar regions was suggested to be rate-limited. However, 
sorption of quinoline into organic matter matrices was not clearly defined in the 
Norborne soil due to the presence of smectite clay minerals. Therefore, column 
studies were conducted on a Eustis soil where a majority of the CEC is located 
in the organic fraction of the soil and the remainder are associated with the 
kaolinitic clay minerals. 

A large drop in effluent concentration («35%) during the 17.8 hr flow 
interruption in the Eustis soil column is indicative of nonequilibrium sorption into 
organic matter matrices (Figure 2-12). It was suggested that sorption of the 
neutral species behaved similarly to HOCs (IOMD), while sorption of the 
quinolinium ion onto exterior regions of organic matter was rapid (cation 
exchange) (Brusseau et al., 1991). However, flow interruption techniques 
enhanced detection of sorption nonequilibrium and suggested that 
nonequilibrium conditions predominated in organic matter matrices (Eustis soil) 
and phyllosilicate minerals (Norborne soil). Access to rate-limited sites was 



67 



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15.5 h 

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10 20 

Pore Volumes (p) 



Figure 2-12. Breakthrough curves of quinoline in Eustis soil with 
0.005 M CaCI 2 and 30% methanol. 



68 
suggested to be faster into the organic matter matrix than into the clay minerals 

(Table 2-3). Organic matter is thought to be a flexible deformable organic 

polymer; therefore, migration into this type of matrix may be less restricted than 

into interlamellar regions of clay minerals. 

Nonequilibrium due to IOMD arises due to restricted diffusion within the 
polymer-like matrix of organic matter (Brusseau et al., 1991). Specific 
interactions of quinoline with functional groups of organic matter are likely to 
change the nature of this flexible organic polymer. Redistribution of charge 
upon migration of quinoline within the organic matter may cause the matrix to 
collapse around the quinoline molecule and restrict diffusion. Brusseau et al. 
(1991) suggested that Ca sorption occurred at the exterior or the organic matter 
because of the long range interaction of electrostatic charge. Alternatively, Ca 
migration into interior regions of organic matter may be rapid. The 
nonequilibrium behavior of quinoline suggests that quinoline migration into the 
interior regions of the organic matter is rate limited. Hydrophobic and cation 
exchange interactions may occur with the quinoline molecule due to charge 
separation on the molecule. 

Figure 2-13 is a proposed schematic diagram of organic matter (Behar 
and Vandenbroucke, 1987). The structure is composed of regions of randomly 
distributed hydrophobic and hydrophilic regions comprised of aromatic and 
aliphatic structures, respectively. Envision quinoline migration into this organic 
matrix: specific interactions between quinoline and hydroxyl groups may occur 



69 




Figure 2-13. Structural representation of organic matter (adapted 
from Behar and Vandenbroucke, 1987). 



70 
followed by redistribution of charge and reconfiguration of the matrix around the 

quinoline molecule. The hydrophobic portion of the molecule may associate 

and partition into the aromatic region. 

Addition of cosolvents increases solubility of organic compounds and 
decreases sorption. In addition, the organic matter matrix may swell, increasing 
accessibility to the interior of the organic matter matrix thereby reducing 
sorption nonequilibrium (Nkedi-Kizza et al., 1989; Lee et al., 1991). However, 
the fraction of instantaneous sites (F) decreased as the matrix swelled because 
the surface area to volume ratio decreases (Lee et al., 1991). 

Other specific solute-solvent and solvent-sorbent interactions increase the 
complexity of describing sorption of ionizable organic compounds in mixed 
solvents systems (Lee et al., 1992). The pK a of acidic functional groups 
associated with the sorbent may increase upon addition of solvents (Lee et al., 
1992). Thus, in the presence of solvents at a given pH, the functional groups 
become more neutral and reduce electrostatic interactions. In addition, the pK 
of the quinoline decreases upon addition of cosolvents. Therefore, at a given 
pH the amount of neutral species present increases. These solvent-sorbent 
and solute-solvent interactions may enhance the migration of molecules within 
the matrix by increasing the permeability and reducing specific quinoline-sorbent 
interactions, thereby reducing sorption nonequilibrium. However, the fraction of 
instantaneous sites may decrease. 

Addition of methanol (30%) reduced quinoline sorption (Figure 2-12). 
Quinoline solubility increases with increasing volume fraction methanol 



71 
corresponding to a decrease in sorption upon solvent addition (Fu and Luthy, 
1986a). Transport parameters for two Eustis soil columns are presented in 
Table 2-3. Cosolvent effects on solubility and sorption of quinoline is 
confounded by specific solvent-sorbent and solvent-solute interactions. The self 
sharpening front is indicative of isotherm nonlinearity. Sorption of quinoline in 
up to 40% methanol was nonlinear (Zachara et al., 1988). However, sorption 
isotherms of pesticides have shown increased linearity upon addition of 
cosolvents (Nkedi-Kizza et al., 1985). 

Direct observation of the organic matter surfaces was attempted by 
taking a scanning electron micrograph (SEM) of an organic soil (Figure 2-14). 
The soil was dried at 60°C and gold coated to prepare the sample. The soil 
was not fixed with glutaraldehyde or dehydrated with solvents to minimize 
structural changes due to fixative agents. The SEM shows the heterogeneity 
association with the surface of organic matter (Figure 2-14a). However, the 
interior of the organic matrix which is the major sink for HOCs is not visualized 
using this technique. We do, however, come to appreciate the complexity of 
the organic surface and the relative scale at which we need to view the organic 
matrix to observe the location of the contaminants within this region. For 
example, the magnification of this SEM is 6000 X. The scale provides reference 
to the size of quinoline. The quinoline molecule conceptualized in Figure 2-10 is 
1 nm in length, suggesting that about 3000 quinoline molecules 
would fit along the scale key. One begins to envision molecules diffusing 
through this heterogeneous media and the concept of rate-limited sorption. 



72 




a 




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jb»; 



■ >• 

&■ '■#! "Jet fir.' '3BT~ 



Figure 2-14. Scanning electron micrograph of an organic soil at 
6000x (a) and 1000x (b). 



73 

The SEM photograph also shows fungal spores that have been preserved 

within this organic soil. Further investigation of the organic matter surface 
revealed fungal mats forming on the organic matter surface (Figure 2-1 4b). The 
prolific growth of fungal spores and hyphal mass depicts the colonization of the 
soil surface by microbial biomass and the possibility of altering contaminant 
sorption and transport. 

Summary 
Quinoline is sorbed predominately on cation exchange sites on clay and 
organic matter. Sorption is therefore dependent on quinoline speciation as 
influenced by pH. Kinetics of ion exchange are rapid; therefore, quinoline 
sorption is controlled by accessibility of sites, most likely through surface 
complexation or inaccessibility due to steric hindrances. Quinoline sorption 
potentially occurs via a three-step process - an initial rapid phase sorbing onto 
instantaneously accessible sites, followed by a reorientation of the molecule on 
the surface, and subsequent redistribution within the organic matrix and 
interlamellar regions of phyllosilicate minerals. Therefore, conceptually the 
bicontinuum model is not adequate to describe quinoline sorption. 

Quinoline sorption within phyllosilicate minerals and organic matter is 
rate-limited. Sorption of quinoline on the outer edges of smectite clay minerals 
may impede access of other quinoline molecules. A buildup of molecules at 
clay interlayers may occur as desorption and migration into interlamellar regions 
is limited. Therefore, access to the interlayer position may be blocked if 



74 
quinoline migration and redistribution is rate-limited. In addition, specific 

quinoline-sorbent interactions (reorientation and charge delocalization) limit 
desorption from the surface. On the other hand, if sorption occurs onto a 
preconditioned quinoline soil containing phyllosilicate minerals access to 
interlayer regions may be enhanced due to compensation of charge by the 
preexisting quinoline. Sorption within organic matter is likely limited by specific 
electrostatic interactions which cause reconfiguration of the organic-type 
polymers. Both sorbents restrict migration into interior regions causing rate- 
limited sorption. 

The bioavailability of quinoline sorbed within either sorbent matrix is likely 
to be limited. As indicated by repeated washing of the Norborne soil, 5 to 10 %, 
of the solute remains sorbed. This fraction is therefore, rendered unavailable to 
the microorganisms based on the location of the solute and the microorganism 
(See Chapter 4 for further discussion). The distribution is microbial biomass in 
the organic soil (Figure 2-14) suggested that microbial biomass may proliferate 
and cover the soil surface. 

The addition of microbial biomass to soils and aquifers may substantially 
alter the nature of the sorbent surface (Figure 2-14). In the absence of 
biodegradation, the impact of biomass on contaminant sorption and transport is 
of great interest. 



CHAPTER 3 
ALTERATION OF SURFACES BY BACTERIAL BIOMASS 



Introduction 

Bioremediation practices attempt to increase microbial activity or populations 
in order to degrade organic contaminants present in soils or aquifers. Indigenous 
microbial activity and/or populations may be increased by providing nutrients 
essential for bacterial growth, or axenic bacterial cultures known to degrade 
specific compounds may be injected directly into contaminated sites. Growth or 
addition of bacteria may drastically alter the chemical and physical characteristics 
of solid surfaces (Fletcher, 1991). Therefore, the impact of bacterial biomass on 
contaminant behavior in porous media near hazardous waste sites is of interest. 

In addition to contaminant biodegradation, addition of bacteria to porous 
media may result in: 1) bacterial growth or transport through the porous media 
leading to pore clogging as a result of physical straining; 2) biosorption and 
bacterial migration facilitating contaminant transport; and 3) bacterial sorption onto 
soil surfaces altering the sorption capacity. Although bacterial migration through 
sandy soils and aquifers is well documented, bioremediation attempts have failed, 
among other reasons, due to the inability of injected bacteria to reach 
contaminated sites (Gibson and Sayler, 1992). Physical, chemical, and microbial 
factors controlling bacterial transport in porous media have recently been 

75 



76 
summarized (Harvey, 1991, Lindqvist and Enfield 1992b, Tan et al., 1992). 

Bacterial transport may be limited by physical constraints imposed by the porous 

media, such as soil structure and pore size distribution (Lindqvist and Enfield, 

1992b). Straining or filtration occurs in soils and aquifers when bacteria are too 

large to pass through soil pores; this results in pore clogging, which restricts 

further penetration of bacteria (Herzig et al., 1970; Harvey, 1991). Once bacteria 

become clogged in the soil pores, water flow is also restricted, and the path of 

water flow can be altered (Vandevivere and Baveye, 1992). 

Chemical constraints, such as adsorption of bacteria, may also limit bacterial 

migration through soils and aquifers (Harvey et al., 1989; Harvey, 1991, Bales et 

al., 1991; Tan et al., 1992). Bacteria that are hydrophobic and are minimally 

charged have the greatest potential to sorb onto surfaces; however, many other 

factors may influence bacterial attachment (van Loosdrecht et al., 1987). Because 

of bacterial adsorption by soils (Daniels, 1972) and clay minerals (Stotzky and 

Rem, 1966), the contaminant sorption capacity of the soil may be altered. Bacteria 

grow after they attach to surfaces if essential carbon and energy sources are 

available. Growth and development of bacterial colonies generally coincide with 

the production of extracellular polysaccharides and promote the formation of 

bacterial biofilms (van Loosdrecht et al., 1990; Fletcher, 1991). Bacterial biomass, 

therefore, contains live and dead cells and cell exudates (extracellular polymers). 

Under nutrient- and substrate-rich conditions, as may be the case near wastes 

sites, biofilm formation may create diffusional barriers leading to nonequilibrium 



77 
sorption of contaminants. This is generally the case for wastewater treatment by 

filtration through activated carbon beds (Speitel et al., 1989; Rittman and McCarty, 
1978). Bacterial biomass may physically alter the accessibility of sorption sites, 
thereby reducing contaminant sorption. To further complicate the problem, 
bacterial biomass may act as an additional sorbent, thereby increasing 
contaminant sorption. 

Sorption by various microorganisms in aquatic systems has been shown for 
hydrophobic organic chemicals (HOCs) (Baughman and Paris, 1981; Tsezos and 
Bell, 1989), metals (Scott and Palmer, 1990), and organic amines (Crist et al., 
1992). A consensus on biosorption mechanisms has not been reached, and 
usually no distinction is made between sorption onto extracellular regions and 
absorption into the cells. Properties such as aqueous solubility and loq K (K 

" ow * ow 

= octanol water partition coefficient) for the contaminant (Selvakumur and Hsieh, 
1988) and bacterial lipid content (Bitton et al., 1988) have been correlated to 
biosorption of HOCs. Biosorption of trace metals has been shown to occur via 
adsorption onto extracellular bacterial capsules with minimal intracellular uptake 
(Scott and Palmer, 1992). Sorption of organic amines by algae has also been 
described by mechanisms including ion exchange and hydrophobic bonding (Crist 
et al., 1992). Occurrence of biosorption and bacterial migration, regardless of the 
underlying mechanisms, suggests the potential for biofacilitated transport of 
contaminants. Lindqvist and Enfield (1992a) demonstrated bacterial-facilitated 
transport of two HOCs (dichloro-diphenyl-trichloroethane and hexachlorobenzene) 



78 
in sand columns. Biosorption technology has been commercialized to mobilize 

metals in the mining industry (Ehrlich and Brierley, 1990). However, biofacilitated 

transport of NHCs bases has yet to be demonstrated. 

Research Question and Tasks 
At the field scale, the question of interest is: what are the consequences 
of bioenhancement or bioaugmentation practices in attempts to remediate 
contaminated sites? Specifically, do bacteria alter the sorption and transport of 
NHCs? In this chapter I examine the impact of bacterial biomass on the 
sorption and transport of three solutes (naphthalene, 45 Ca, and quinoline) in a 
subsurface soil. These compounds were selected because of their known 
specific interactions in soil: 1) naphthalene was selected to probe hydrophobic 
interactions with the nonpolar organic phase; 2) 45 Ca was selected to probe 
electrostatic interactions with the cation exchange sites; and 3) quinoline, a N- 
heterocyclic organic base, was selected because it can exist as a neutral 
organic compound interacting with the organic phase or as a quinolinium ion 
interacting with cation exchange sites. Miscible displacement techniques were 
used to measure sorption and transport of the above compounds during 
steady, saturated water flow conditions through homogeneously-packed, sterile 
or bacterial-inoculated, soil columns. A fine-textured silt loam soil (Norborne; 
fine-loamy, mixed, mesic Typic Argiudoll) was chosen for these experiments 
because of the extensive characterization of quinoline sorption by this soil 
(Zachara et al., 1988; 1990). Sorption of naphthalene by the organic fraction of 



79 
soil is well documented (Chiou et al., 1983; Karickhoff et al., 1979). Pre- 

inoculation of the Norborne soil with bacteria (10 8 cfu/g) simulates 

contaminated subsurface soils and aquifers where bacterial populations may be 

high. 

Materials and Methods 
Sorbents 

The Norborne soil was used for these studies (Table 2-1). Glassbeads 
(average diameter 150 /xm; Alltech Associates) and inert quartz sand (< 2 mm) 
were used as inert solid support material. All sorbents were sterilized using 
steam autoclaving as referenced in Chapter 2. 

Sorbates 

Pentafluorobenzoic acid (PFBA; 150 /ig/mL) was used as conservative, 
nonsorbing tracer to assess the hydrodynamic dispersion and extent of physical 
nonequilibrium conditions prevailing during transport through the soil columns 
(Brusseau et al., 1989). Quinoline and naphthalene concentrations in the 
influent solutions for the column studies ranged from 4 to 10 iig/mL. Isotopic 
exchange of 40 Ca and 45 Ca (6,000 dpm/mL) was also investigated. Aqueous 
solutions of the chemicals were prepared in filter-sterilized (0.2 Mm) 0.005 or 
0.05 M CaCI 2 . Sorbates were monitored by HPLC-UV for quinoline and 
naphthalene, and by radio-assay techniques for 45 Ca (See Chapter 2). 



80 
Bacterial Strains and Culture Conditions 

A strain of Pseudomonas sp. 3N3A capable of degrading quinoline and a 
mutant strain (B53) derived from the 3N3A strain [obtained from Brockman et 
al. (1989)]. Incorporation of two proteins for bacterial enumeration rendered the 
organism incapable of degrading quinoline (McBride et al., 1992). The B53 
isolate was used to determine the impact of biomass on sorption and transport 
of quinoline where degradation was not a factor. 

The B53 and 3N3A strains were grown for 17.5 hours on tryptic soy 
broth (3 g/L) at 28° C on a rotary shaker (100 rpm). Bacterial cells were 
harvested by centrifugation, washed two times and diluted to the desired 
bacterial density with the appropriate background matrix solution (0.005 or 0.05 
M CaCI 2 ). Bacteria were allowed to equilibrate overnight in the desired matrix 
prior to each experiment. Plate counts were done using tryptic soy agar (TSA) 
and 4 day incubation periods at 28°C. Plate counts were verified by visual 
inspection of bacterial suspensions using a hemacytometer. A phase-contrast 
microscope (Wild Neenbrugg) was used for counting the bacteria in the 
hemacytometer. 

Bacterial Inoculation 

A 0.5 mL-aliquot of the appropriate bacterial suspension was placed in 
an aspirator. The sterile soil (50 g) was thinly spread on aluminum foil and the 
bacterial suspension was sprayed on the soil in a fine mist to uniformly 
distribute the bacteria. The soil sample was mixed thoroughly to ensure 



81 
homogeneous distribution of the bacteria. The aspirator was rinsed with a 0.5- 

ml_ aliquot of filtered (0.2 /xm) CaCI 2 , and the rinsate was sprayed on the soil. 

The initial inoculation rate was 10 6 cfu/g soil unless otherwise indicated. The 

soil was mixed again, and a subsample was taken for water content 

determination. The soil-water content following bacterial addition ranged from 5 

to 10%. 

Column Studies 

Miscible displacement techniques were used to characterize the transport 
of PFBA, 45 Ca, quinoline, and naphthalene. The sterile or bacterial inoculated 
soil was packed into a Kontes glass column (5 cm long, 2.5 cm i.d.) as 
described in Chapter 2. After packing, approximately 150 pore volumes of 
0.005 or 0.05 M CaCI 2 solution were pumped through the column to achieve 
saturated, steady water flow conditions and uniform bacterial populations (10 8 
cfu/g). Soil columns varied in bacterial density and type (sterile, or inoculated 
with either B53 or 3N3A isolate) and in ionic strength (0.005 or 0.05 M) of the 
displacing solution. Solute concentrations were monitored continuously or by 
collecting column effluent fractions. Dissolved oxygen (DO) in the soil column 
effluent was measured at different pore-velocities from 0.6 to 90 cm/hr. A 
vessel was purged with N 2 , effluent from the column introduced, and DO 
measured with a dissolved oxygen electrode (Yellow Springs Instruments 5750). 

Sorption of quinoline by live cells of the B53 and 3N3A isolates was 
measured at a bacterial density of 10 8 cfu/mL The initial quinoline 



82 
concentrations were 1 , 4, and 8 Mg/mL Bacterial suspensions were 

equilibrated with quinoline at 5° C for 1 hr to minimize intracellular uptake and 

possible biodegradation by the 3N3A isolate. Biosorption of 45 Ca was 

measured at room temperature (22-25°C). Samples were centrifuged for 20 

min at 1 ,250 g at 5°C to separate the cells from the aqueous phase. Quinoline 

solution concentrations were measured by HPLC to monitor for possible 

biodegradation products. Biosorption was calculated as the difference in the 

initial and final solution concentrations. Miscible displacement techniques 

described earlier were employed to measure biosorption by bacteria "attached" 

to glass microbeads. Glass microbeads (average diameter 150 /im; Alltech 

Associates) were inoculated with 10 7 cfu/g, packed into a column, and 

saturated with 0.05 M CaCI 2 for 48 hours at a pore-water velocity of 13.5 cm/hr. 

BTCs for quinoline, 45 Ca, and naphthalene were measured simultaneously by 

injecting a mixture of these three solutes on the column; this was done so that 

BTCs for all three solutes were obtained under identical hydrodynamic and 

microbial conditions. Effluent fractions were collected and monitored by the 

techniques stated above. 

Surface Accessibility 

A comparison of the estimated values of the bicontinuum sorption model 
parameters (Chapter 1 and 2) for the sterile and inoculated soil columns were 
used for a quantitative assessment of: 1) the hydrodynamic impacts, based on 
P; 2) the changes in equilibrium sorption capacity, based on K ; and 3) the 
accessibility of sorption regions, based on F and k 2 . 



83 

Results 

The behavior of PFBA in sterile and bacterial-inoculated columns is 
represented by the PFBA breakthrough curve (BTC) in Figure 3-1. BTCs for 
quinoline (0.005 M CaCI 2 ) in a sterile and inoculated (B53 and 3N3A isolates) 
columns are also shown in Figure 3-1. BTCs for 45 Ca and naphthalene (0.05 M 
CaCI 2 ) in sterile and inoculated B53 columns are shown in Figure 3-2 and 3-3, 
respectively. The PFBA BTCs for all soil columns were symmetrical and sigmoidal 
in shape, which suggests the absence of physical nonequilibrium (Brusseau and 
Rao, 1989b), and P > 98 is indicative of minimal hydrodynamic dispersion. 
Quinoline and naphthalene sorption was reduced in inoculated soil columns 
(Figures 3-1 and 3-3). 45 Ca sorption (Figure 3-2) was not reduced in the B53 
inoculated soil columns. The shift in the 45 Ca BTC in the two bacterial-inoculated 
soil columns (BQ11 and BQ112) and the sterile column (B) resulted from 
differences in the bulk densities (p) and volumetric water contents (6) of the 
various columns (Table 3-1). Therefore, direct comparison of R for different 
columns is misleading. The impact of bacteria on sorption and transport of 
quinoline, 45 Ca, and naphthalene was assessed by comparing the Kf values in 
sterile and inoculated columns. The Kf values verified that sorption of quinoline 
and naphthalene was reduced in inoculated columns, whereas 45 Ca sorption was 
not significantly different. 

The following results are from a series of experiments that were conducted 
to deduce the causes of reduced quinoline and naphthalene sorption. Experiments 



84 



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Quinoline: 

• Sterile (B) 

* 3N3A (BQ6) 
°B53(BQ9) 



■ PFBA 



5 10 

Pore Volumes (p) 



15 



Figure 3-1. Measured BTCs for PFBA (■) in a sterile column and 
for Quinoline in a sterile (•), 3N3A inoculated (*), and 
B53 inoculated (□) soil column. Column designations 
are given in parenthesis corresponding to Table 3-1 . 



85 



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3 


— S» 


* • 
* • 5), at 

» Arf — i * *°*f t)» i « i 



5 10 

Pore Volumes (p) 



15 



Figure 3-2. Measured BTCs for 45 Ca in sterile (•) and B53 
inoculated (o and *) soil columns. Column 
designations are given in parenthesis corresponding to 
Table 3-1 . 



86 

















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Pore Volumes (p) 



15 



Figure 3-3. Measured BTCs for Naphthalene in a sterile (•) and a 
B53 inoculated (o) soil column. Column designations 
are given in parenthesis corresponding to Table 3-1. 



87 



Table 3-1. Column parameters and Kj values for quinoline, naphthalene, and 



45 



Ca in sterile and inoculated Norborne soil columns. 



Column ID mol/L pH g/cnr cirr/crrr Quinoline Naphthalene 45 Ca 



CaCI, 



e 



Kf 



Sterile, BQ5 0.005 7.0 1 

Sterile, B 0.05 7.0 1 

B53, BQ9 0.005 6.8 1 

B53, BQ11 0.05 6.6 1 

B53, BQ112 0.05 6.7 1 

3N3A, BQ6 0.005 6.9 1 



.48 


0.44 


3.11 


.54 


0.42 


3.11 


.46 


0.45 


1.39 


.44 


0.41 


1.05 


.44 


0.46 


— 


.39 


0.46 


2.42 



0.946 



0.555 



10.0 
1.17 

1.05 
1.06 



focused on distinguishing between the processes that may influence 
contaminant sorption and transport including altered water flow resulting from 
pore blockage, biofacilitated contaminant transport, and/or altered sorption 
capacity of soil. 



Pore Blockage 

Pore blockage or straining of bacteria was investigated by measuring 
BTCs for a nonadsorbed tracer (PFBA) once a day for 7 days following 
bacterial inoculation. Variations in pore volume determinations or asymmetrical 
BTCs would indicate changes in physical characteristics of the column. In all 
cases, the BTCs measured for PFBA were symmetrical (indicative of no 
changes in hydrodynamic characteristics) and the pore volume determined by 



88 
PFBA remained constant (indicative of no blockage or exclusion of some 

pores). Therefore, eariy breakthrough of quinoline and naphthalene was not 

the result of pore blockage by bacterial biomass. 

Biofacilitated Transport 

Bacterial migration . Biofacilitated transport required verification of 
bacterial migration and biosorption. Bacterial migration in the Norborne C soil 
was investigated by packing the outlet half (2.5 cm) of a column with sterile soil 
while the inlet half (2.5 cm) was packed with B53 inoculated soil (10 6 cfu/g). 
The appearance of 300 cfu/mL in effluent fractions after displacement of 75 
pore volumes verified bacterial migration through a half sterile and half 
inoculated Norborne soil column. Bacterial counts were similar using plate 
count techniques and by visual inspection using a hemacytometer. Therefore, 
bacterial populations were subsequently determined by plate counts. After 7 
days of flow (13.5 cm/hr), the column was sectioned into 1-cm segments and 
bacteria were extracted with a pH 7.3 phosphate saline solution which was 
recommended as a standard microbial technique (Wollum, 1982). The soil- 
saline suspension was diluted, allowing the soil to settle, and plated. The 
bacterial density was 10 8 cfu/g at the inlet end of the column, 10 7 cfu/g in the 3 
center sections of the column, and 10 6 cfu/g at the end of the column. Three 
observations noted were: 1) increased bacterial densities verified bacterial 
growth; 2) populations decreased from the inlet to the outlet end of the column 
in response to inoculation of the inlet 2.5 cm of the column; and 3) bacteria 



89 
migrated and populated the entire column with the maximum population 

reaching 10 7 to 10 8 cfu/g. Maximum bacterial effluent concentrations ranged 

from 10 4 to 10 5 cfu/mL, confirming bacterial transport. 

The bacterial population in the soil column was supported by nutrients 
and organic carbon released from the soil matrix. Analysis of the column 
effluent confirmed the presence of trace quantities of essential elements for 
bacterial growth. Therefore, additional nutrients were not supplemented (for 
further discussion see Chapter 4). Energy was likely derived from the dissolved 
organic carbon in the soil solution. Assuming a maximum bacterial population 
of 10 8 cfu/g, bacterial dry weights of 16 * 10" 13 g/cfu (Gray et al., 1974), and 
50% of the bacterial cell is organic carbon (Bratbak and Dundas, 1984), 8 * 10" 5 
g of organic carbon is required to maintain this population. The available 
dissolved organic carbon (DOC) from soils has been estimated to be about 1% 
of the total organic carbon (Reddy et al., 1982). Therefore, about 1.6 * 10~ 5 g 
DOC per ml_ of soil solution providing may have been available, which can 
provide adequate energy for bacterial cell production. 

Water flow may alter bacterial movement and the dissolved oxygen (DO) 
content, which in turn may influence the activity of microorganisms (Smith et al., 
1985; Trevors et al., 1990; Lindqvist and Bengtsson, 1991). Therefore, DO was 
measured at different velocities. A vessel was purged with N 2 , effluent from the 
column introduced, and DO measured with a dissolved oxygen electrode 
(Yellow Springs Instruments 5750). In the Norborne soil columns, DO ranged 



90 
from 0.5 to 2 mg/L in the column effluent and increased with an increase in 

velocity (6 to 90 cm/hr). As a result, subsequent experiments were conducted 

at about 15 cm/hr. Transport of bacteria through the soil column is a 

necessary, but not a sufficient, condition for claiming biofacilitated transport of 

contaminants. It was also necessary to establish that the contaminant was 

sorbed to an appreciable extent by the bacterial biomass. 

Biosorption . Quinoline and 45 Ca biosorption by the 3N3A isolate or its 
mutant B53 was not measurable at 5°C or room temperature (22-25°C) using 
batch techniques. However, variations in pH, nutrients, and availability of 
surfaces may alter the sorptive characteristics of microbial surfaces (Beveridge 
and Graham, 1991). Therefore, biosorption of quinoline and 45 Ca was 
determined directly in column experiments. Filtration (0.2 jxm) of the column 
effluent to separate biosorbed (trapped with the biomass on the filter) and free 
species (in the filtrate) showed no reduction in the solution concentration or 
accumulation on the filter. Therefore, biofacilitated transport of quinoline and 
45 Ca by bacteria in the solution phase was not likely. 

The extent of 45 Ca, quinoline, and naphthalene biosorption by adsorbed 
bacteria was determined by BTCs measured in a column packed with glass 
microbeads and inoculated with the B53 isolate (10 7 cfu/g). Miscible 
displacement techniques are preferred for estimating sorption parameters, 
especially in low-sorptive systems (Brusseau et al., 1991) (i.e., small K ). The R 
for quinoline, 45 Ca, and naphthalene in a sterile, glassbead column was 



91 
approximately 1 , indicating no sorption of these solutes by glassbead surfaces. 

Thus, any retardation measured in the inoculated glassbead column is 
attributed to biosorption by the attached bacteria. Biosorption was small for 
* 5 Ca (R = 1.15) and quinoline (R = 1.16) corresponding to a K « 0.04 mL/g, 
while naphthalene biosorption was slightly greater (R = 1.29; K « 0.06 mL/g) 
(Figure 3-4). These results suggest that biofacilitated transport of 45 Ca, 
naphthalene, and quinoline is not likely to be important in our studies, unless 
high densities (> 10 8 cfu/mL) of bacterial biomass are sloughed off into the 
column effluent. 

Bacterial populations in the effluent of glassbead columns were 10 6 to 
10 7 cfu/mL, which was higher than populations in the Norborne soil columns 
(10 5 cfu/mL). The increased bacterial populations may have been due to a 
larger pore size or a reduction in the sorption capacity of the glassbeads versus 
the Norborne soil. Sorption of bacteria on glass surfaces and mechanisms of 
attachment have been documented (Heukelekian and Heller, 1940; Zobell, 
1943; Stotkzy, 1985; van Loosdrecht et al., 1990; Marshall, 1992). Therefore, 
larger pore size within the glassbead column likely reduced physical constraints 
and facilitated bacterial migration. Thus, biofacilitated transport may 
predominate in porous sandy aquifer material. Enhanced bacterial migration 
caused coatings to form on the UV detector cell which interfered with flow- 
through detection of the column effluent. This suggests that fraction collection 
is essential to avoid analytical complications in porous media which are 



0.8 



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92 



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* 



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Glassbead Column 



o 



o 
□ 



o 



Naphthalene 



• 45 



Ca 



D Quinoline 
* PFBA 



-+— D 



*"*- 



Pore Volumes (p) 



Figure 3-4. Measured BTCsfor PFBA (*), 45 Ca (®), Quinoline (□), and 
Naphthalene (o) in a B53 inoculated soil column. 



93 
inoculated with bacteria. Therefore, biosorption of quinoline and 45 Ca was 

determined directly in column experiments. Filtration (0.2 /xm) of the column 

effluent to separate biosorbed (trapped with the biomass on the filter) and free 

species (in the filtrate) showed no reduction in the solution concentration or 

accumulation on the filter. Therefore, biofacilitated transport of quinoline and 

45 Ca by bacteria in the solution phase was not likely. 

Surface Blockage 

Alterations of soil surfaces by the addition of microorganisms may occur 
directly as a result of bacterial sorption onto surfaces. Therefore, the potential 
for 3N3A and B53 isolates to adhere onto surfaces was determined by 
measuring their electrophoretic mobility and hydrophobicity. Electrophoretic 
mobility of the bacteria was measured in a mineral salt solution used by 
Brockman et al. (1989). The zeta potential of the 3N3A and B53 isolates was 
determined using a Laser Zee Meter (PENKEM Model 501). The bacterial- 
buffer solution («30 ml_) was placed in an electrophoresis chamber consisting 
of two electrodes and a connecting chamber. The rate of bacterial movement 
in a known electric field was monitored through a microscope with a 20x 
objective lens and a 15x ocular lens. All measurements were made in the 
stationary layer to avoid flow in the boundary layers. Zeta potential was 
converted to electrophoretic mobility using the Helmholtz-Smoluchowski 
equation (Sherbet, 1978). The electrophoretic mobility of the 3N3A isolate 
ranged from -1.0 to -1.5 10~ 8 meter/V/sec from pH 4 to 8.5. Over the same pH 



94 
range, the electrophoretic mobility of the B53 isolate ranged -0.5 to -1.0 10~ 8 

meter/V/sec. These values are in agreement with electrophoretic mobilities 

measured over the same pH range (Krekeler et al., 1991) and electrophoretic 

mobilities (-0.42 to -3.42 10~ 8 meter/V/sec) measured for 23 bacterial isolates 

(van Loosdrecht et al., 1987). The lower negative charge of the B53 isolate 

suggests that it has a greater potential than 3N3A to approach the soil surface 

and attach. 

The relative bacterial hydrophobicity of the bacterial isolates was 

determined by partitioning the bacterial isolates between hexadecane and a 

phosphate buffer solution following the procedure used by Rosenberg et al. 

(1980). Bacterial cells which partition into the hexadecane phase from the 

aqueous phase indicated that bacterial surfaces are hydrophobic. The 

hydrophobicity (e.g., adsorption potential) was assessed by the bacterial 

distribution coefficient between the hexadecane phase and the aqueous phase 

(D HW ). At pH 7.5, the D HW was 3 times larger for the B53 isolate (D HW = 0.39 

mL/mL) than the 3N3A isolate (D HW = 0.12 mL/mL). However, at pH 6.5 the 

D HW was 10 times larger for the B53 isolate (D HW = 0.11 mL/mL) than the 

3N3A isolate (D HW = 0.01 mL/mL). The hydrophobicity of the B53 isolate is 

greater than the 3N3A isolate in the pH range of the soil columns. Both 

hydrophobic and electrostatic interactions favor sorption of the B53 isolate. 

Given that bacteria may attach, grow, and colonize the surface, the potential 

exists to alter the soil surface and more specifically the soil sorption capacity. 



95 
Evidence for alteration of the soil surface by bacterial biomass was 

suggested in an inert quartz sand (<2 mm) column. The effluent pH from a 

B53-inoculated quartz sand column was 4.65 upon introduction of PFBA (pK Q = 

1 .59) while the pH of PFBA passing through the sterile quartz sand column was 

pH 3.2. The quartz sand has no appreciable buffer capacity for maintaining the 

pH of the acidic PFBA solution. Therefore, the pH increase in the column 

inoculated with bacteria suggests that the bacterial biomass altered the soil 

surface environment (e.g., bacteria have an inherent buffer capacity). Changes 

in bulk solution pH were not observed for the experiments with the Norborne 

soil column because of the larger buffer capacity of this soil. This does not, 

however, preclude the possibility that alteration of pH had occurred within the 

interfacial regions for the Norborne soil. Since it is difficult to measure any 

changes in interfacial pH directly, we can only infer here the trends based on 

observed effects on quinoline sorption by the Norborne soil. 

Approximately 50% of quinoline sorption occurred within the interlayer 

positions of phyllosilicate minerals. Microorganisms are unable to access 

interlamellar regions of clay minerals due to size constraints. As a result, only 

50% of the sorptive region is directly in contact with bacterial biomass. 

Extracellular polymers may be released and migrate within interlamellar clay 

regions. However, the influence of bacterial biomass is likely indirect. 

Processes such as respiration consume oxygen and release of C0 2 likely 

decreasing pH which would increase sorption. Simultaneously, a decrease in 



96 
pH may cause a decrease in cation exchange capacity. The surface area of 

the bacterial biomass is five orders of magnitude smaller than the external soil 

surface area. Therefore, the distribution of bacteria on the soil surface and their 

relation to the sorptive region is important. 

The addition of bacteria influenced quinoline retention more than the 

sorption of naphthalene or 45 Ca. Therefore, quinoline was used to further 

investigate the differences between the effects of 3N3A and B53 isolates on 

sorption and transport. The presence of the B53 isolate reduced the sorption 

of quinoline by about 60%, and 3N3A reduced quinoline sorption by about 20% 

(Table 3-1). Despite the differences in inoculation rate (10 6 cfu/g 3N3A, 10 5 

cfu/g B53), the early quinoline breakthrough in inoculated (B53 versus 3N3A) 

columns was not likely due to variations in bacterial populations. To test the 

above hypothesis, soil columns were inoculated with the B53 isolate at 10 5 , 10 6 , 

and 10 7 cfu/g. Quinoline BTCs measured in each case were similar. 

Saturation of the soil columns prior to conducting the quinoline BTCs resulted in 

growth and colonization of soil surfaces. Bacterial densities of 10 8 cfu/g were 

supported in the Norborne soil independent of the initial inoculation rate and 

bacterial isolate. As a result, the differences in quinoline BTCs measured in the 

inoculated (3N3A and B53) soil columns were attributed to microbial surface 

characteristics and their impact on the soil surfaces. 

Surface Accessibility 

An attempt was made to use the bicontinuum model to quantitatively 
assess the impacts of bacterial biomass on the physical accessibility of sorptive 



97 
regions in the soil. However, bicontinuum sorption model analysis of the BTC 
data was attempted only for the naphthalene BTC data for the following 
reasons: 1) unpublished data suggests that quinoline sorption dynamics are 
more complicated than that conceptualized in the bicontinuum model; and 2) 
cation exchange kinetics are rapid enough that the bicontinuum model is not 
needed to describe 45 Ca BTCs; an equilibrium sorption model provides an 
adequate description (Brusseau et al., 1991). 

The bicontinuum sorption model was used to fit the naphthalene BTC 
data and to evaluate the alterations in accessibility to sorptive regions of soil. 
About 60% (F= 0.63) of naphthalene sorption was surmised to have occurred 
instantaneously in the sterile soil, while F decreased to 0.33 in the inoculated 
column. About 50% reduction in the F value suggests that the accessibility of 
sorption regions to naphthalene had been reduced due to the presence of 
bacterial biomass. The k 2 (1.66 hr~ 1 ) and K (0.946 mL/g) from the sterile 
column are in agreement with the log-log-linear inverse relationship between log 
k 2 and log K values (log k 2 = 0.301 - 0.668 log K ) reported for sorption of 
HOCs (Brusseau and Rao, 1989a). However, the k 2 value estimated from the 
naphthalene BTC measured in the inoculated soil column was about a third of 
that for the sterile column (0.52 vs. 1.66 hr" 1 ), which is indicative of further 
constraints on naphthalene sorption. The analysis of model parameters 
suggests the following: 1) an overall reduction in naphthalene sorption 
(decrease in K ); and 2) a decrease in accessibility of sorption regions 
(decrease in both F and k 2 ). 



98 

Discussion 

The specific sorption mechanism for a solute may influence the impact of 
the microbial biomass on contaminant sorption and transport. For example, a 
compound undergoing electrostatic interactions, such as cation exchange, 
would exhibit reduced sorption if the specific exchange sites were inaccessible. 
Similarly, HOC sorption may be reduced if the biomass is less hydrophobic and 
reduces access to organic regions in which a nonpolar compound is sorbed. 
On the other hand, sorption of HOCs may increase if hydrophobic biomass 
remains on the soil surface and increases the overall hydrophobic nature of the 
soil. If, however, hydrophobic biomass is transported in the solution phase 
biofacilitated transport may occur. For ionogenic compounds, bacterial 
biomass may cause interfacial variations in pH which would alter their sorptive 
behavior. 

The premise that bacterial biomass alters sorption of contaminants 
requires further definition of the locations of contaminant sorption as well as the 
bacterial colonies. This question is of great interest in remediation of 
contaminated soils and bioavailability of contaminants. However, the answer is 
not readily available. To facilitate the discussion, the following assumptions will 
be made: 1) HOC sorption is assumed to occur within the organic fraction of 
the soil; 2) sorption of cations occurs predominantly on cation exchange sites 
located within clay interlayers and aggregates; 3) bacteria colonize soil surfaces 
as microcolonies (Vandevivere and Baveye, 1992; Marshall, 1992); and 4) 



yy 
bacteria are assumed to adhere to soil surfaces in collocation with the energy 

and nutrient sources (e.g., organic matter and clay). The presence of bacterial 

biomass in soil may impact contaminant sorption directly by decreasing the 

accessibility of sorptive regions or indirectly by changing the interfacial 

properties of the soil. 

Biofacilitated Transport 

Biosorption of quinoline and 45 Ca was not measurable; therefore, 
biofacilitated transport did not likely reduce retardation of these compounds. 
Naphthalene biosorption may have occurred in the column studies resulting in 
biofacilitated transport in the inoculated columns. HOCs possessing a more 
hydrophobic nature are more apt to undergo biosorption, and therefore, 
biofacilitated transport. For example, DDT, a highly hydrophobic chemical, was 
strongly sorbed in sterile sand columns (R = 59.8), but displacement of 
bacterial solutions containing DDT through the sand columns demonstrated 
biofacilitated transport in which R was reduced 8-fold (Lindqvist and Enfield, 
1992a). Biofacilitated transport may be most important in contaminated sites, 
where bacterial populations and chemical concentrations are high and for 
chemicals exhibiting high biosorption potential. However, initial incubation of a 
contaminant with the soil prior to bacterial addition may reduce the potential for 
biofacilitated transport due to rate-limited contaminant desorption. 



100 
Surface Alteration 

Assuming that quinoline and 45 Ca access the same cation exchange 
sites, sorption of 45 Ca and quinoline should be reduced to the same extent if 
bacterial microcolonies developed and access to exchange sites was 
inaccessible. Quinoline and 45 Ca sorption was not reduced in a similar manner, 
suggesting that biomass did not substantially alter the cation exchange capacity 
of the soil. Biomass impacts on sorption were solute specific, even when the 
sorption sites for both quinoline and 45 Ca are similar. Thus, the differential 
response is attributed to biomass-induced changes in quinoline speciation; an 
increase in pH at the sorbent-water interface would result in a larger proportion 
of the neutral species, and a decrease in sorption. Stucki et al. (1992) suggest- 
ed that microbial biomass modifies the redox status of clay minerals resulting in 
charge destabilization and subsequent collapse of clay layers. Alteration of soil 
properties and the soil-solution interface by bacterial biomass may impact the 
behavior of ionogenic and inorganic compounds. The combination of biomass- 
induced changes in quinoline speciation and inaccessibility of sites likely 
reduced quinoline sorption. Bacterial biomass may contribute to the measured 
increase in naphthalene sorption by adding hydrophobic microbial biomass to 
the soil. Bacterial populations in the soil columns were about 10 8 cfu/g soil. 
Although plate counts possibly underestimated the total number of cells, it was 
reasonable to believe that 10 8 cfu/g were supported in the soil columns. The 
corresponding bacterial f_„ was 8 * 10" 5 and the soil had an f of 0.0016. In 

uu oc 



101 
this case, bacterial biomass added about 1% to the soil sorption capacity. 

Therefore, the bacterial biomass may not have contributed substantially to the 

organic carbon content. However, in low organic matter soils or sandy aquifer 

materials, contaminant sorption may be increased upon bacterial additions. 

Whereas, quinoline and 45 Ca sorption was reduced by the addition of bacterial 

biomass, naphthalene sorption may have been decreased by surface 

inaccessibility and biofacilitated transport or slightly increased by the addition of 

organic matter to the soil. The counteracting effects of these mechanisms likely 

decreased the magnitude of enhanced naphthalene transport. 

Surface Accessibility 

Addition of bacterial biomass and production of extracellular bacterial 
polymers (Kjelleberg et al., 1984; Bengtsson, 1991; Vandevivere and Baveye, 
1992) may alter the ability of Norborne soil to sorb chemicals. This soil has a 
low organic carbon content (0.16%) and electrostatic interactions are primarily 
associated with the 2:1 clay interlayer positions. Bacterial biomass may have 
altered sorption of quinoline in intra-aggregate and interlamellar regions. 
Reduced accessibility of organic matter by bacterial biomass decreased 
naphthalene sorption. 

Summary 
The impact of biomass on the sorption and transport of contaminants 
was investigated. Sorption of NHCs was shown to be reduced as a result of 



102 
speciation changes at the soil-solution interfaces which were induced by 

bacterial biomass. The sorption of an inorganic cation (calcium) was not 

affected by the presence of bacterial biomass, suggesting that blockage of 

cation exchange sites was minimal. HOC sorption was slightly reduced due to 

a combination of processes including blockage of organic regions by 

hydrophilic bacteria and biofacilitated transport. Naphthalene has a log K of 

about 2 and biofacilitated transport was not substantial. However, compounds 

with log K ow values (>6) are more likely to sorb onto bacteria and thus, their 

transport can be enhanced. 

Near waste disposal sites, microbial populations and colonization of 

surfaces is likely. Therefore, enhanced contaminant transport may occur either 

due to biomass-induced speciation changes of sorbent surfaces or biosorption 

and biofacilitated transport. Stimulation of bacterial growth activity as a result of 

bioremediation practices may enhance contaminant transport if conditions for 

biodegradation are not favorable. Understanding the factors that influence 

biodegradation are necessary to overcome the limitations of bioremediation 

practices such that contaminants are removed to the desired concentration. 



CHAPTER 4 
QUIN0L1NE BIODEGRADATION IN FLOW-THROUGH SYSTEMS 



Introduction 
Solute-Sorbent Impacts on Biodearadation 

Bioavailability and biodegradation are dependent upon solution-phase 
concentrations of contaminants which are controlled by sorption-desorption 
processes, and bacterial associations with the sorbent and contaminant. The 
principal hypothesis concerning the impact of sorption of biodegradation is that 
sorbed substrates are unavailable to bacteria. This hypothesis is contingent 
upon the occurrence of intracellular degradation. The distribution of bacteria in 
relation to the location of the contaminant may also influence the likelihood of 
biodegradation. A majority of the bacteria exist in discrete microcolonies on 
surfaces in soil and aquifer materials and some bacteria (10%) exist in the 
solution-phase. 

Bioavailability of sorbed contaminants has been the primary focus of 
recent research efforts since the success of bioremediation practices is 
predicated on contaminant release from the sorbed-phase. Several questions 
need to be answered to understand the coupling of sorption and 
biodegradation: 1) Is the process intra- or extracellular? 2) Is sorption reversible 
or irreversible? 3) Where does the contaminant reside, within the sorbent matrix 

103 



104 
or on the surface? and 4) Where are the microorganisms and does their activity 

change while they are attached to surfaces or in the solution-phase? Some of 

these questions have previously been addressed. However, after reviewing the 

literature it becomes more obvious that this interdisciplinary problem needs 

further resolution. 

The speculation of the impact of sorption on biodegradation from 
experimental data requires a full understanding of the aspects of contaminant 
sorption and biodegradation processes. Consider the following two scenarios 
to address the previous questions. In Case 1 , hydrolysis of urea occurs via 
extracellular enzymes. For discussion purposes, assume that urea is sorbed on 
the sorbent surface and is hydrolyzed by sorbed extracellular enzymes. In this 
case, the enzymes exist in collocation with the substrate, becoming more 
bioavailable. However, if the enzymes are sorbed and fixed to the soil surface 
they may be separated from the substrate and only have access to substrates 
flowing by in the solution phase. Sorption may also "deactivate" the enzyme 
due to structural rearrangement. Urea that is sorbed within the interior regions 
of the sorbent matrix is likely unavailable due to restricted access of the 
enzyme, and hydrolysis is thereby limited by urea diffusion out of the sorbent 
matrix. As a result, urea hydrolysis may be the result of enzyme-urea 
interactions occurring only in the solution phase. 

Consider another example, Case 2, sorption of the contaminant occurs 
within the organic matter matrix or phyllosilicate mineral and biodegradation 



105 
occurs intracellularly. Microorganisms may be excluded from most pores within 

the sorbent matrices. Biodegradation, in this case, is limited by mass transfer 

of the solute from the interior of the sorbent to the exterior solution. This 

scenario is often used to describe biodegradation limited by intraparticle 

(Chung, et al., 1993; Scow and Alexander, 1992) or intraorganic matter 

diffusion. For several HOCs and a few ionic compounds (e.g., diquat), mass 

transfer has been shown to limit sorption/desorption rates and biodegradation 

(See Chapter 1). 

A majority of organic contaminants are degraded intracellularly, therefore, 
desorption of contaminants is required for microbial uptake and subsequent 
biodegradation. Sorption of HOCs is generally reversible (Chiou et al., 1983), 
whereas contaminants such as diquat may become irreversibly bound within 
interlayers of clay minerals (Weber and Coble, 1968). For HOCs, the total 
contaminant degraded should not be limited by sorption unless enzymes 
necessary for biodegradation are not sustained. 

Figure 4-1 presents a schematic view of the spatial arrangement of 
microorganisms and solutes in a soil aggregate. The sorbed-phase solute (S) 
is located primarily within the sorbent matrix. The concentration of solute in the 
pore water (C ) and bulk solution-phase (C) is dependent on the sorption 
capacity of the soil and the microbial biodegradative capacity. Microorganisms 
exist predominantly on the external surface of soil particles or aggregates. 
Upon growth, microorganisms may slough off into the solution-phase. As soil 



106 



Organic 
Matter 

Clay 

Mineral 



Microorganisms 



_ Metabolism 
c ► 




Figure 4-1. Schematic of sorption and biodegradation in soil 
aggregates (C and C = the solute concentration in 
the pore water inside the aggregate and the bulk 
solution, respectively) (adapted from Mihelcic and 
Luthy, 1988c). 



107 
aggregates are formed, microorganisms may become trapped within the soil 

aggregate. However, the biodegradation by aerobic microorganisms is likely 

reduced or stopped upon depletion of oxygen within the aggregate. Size 

constraints limit migration of microorganisms within the soil aggregate. 

Therefore, intracellular biodegradation by aerobic microorganisms likely occurs 

in the bulk solution-phase resulting in diffusion-limited biodegradation from 

aggregates or sorbent matrices found in soil-water suspensions. The 

contaminant residing within the interior of the aggregate, organic matrix, or 

phyllosilicate mineral is not readily available for biodegradation. 

Several models considering diffusion- and desorption-limited 

biodegradation have been developed for batch and column techniques. Scow 

and Hutson (1992) developed a diffusion-sorption-biodegradation (DSB) model 

describing diffusion-limited biodegradation of contaminants out of interior 

regions of aggregates in a batch system. Figure 4-2 presents simulations of the 

influence of sorption partition coefficients on the biodegradation of solutes 

diffusing out of an aggregate with a radius of 0.05 cm. The final mass 

degraded approaches a constant value and only the rates of approach are 

decreased with increasing sorption coefficient value. Interpretation of this 

simulation would suggest that biodegradation is diffusion limited. Figure 4-3 

presents data and DSB model simulations for glutamate from gel exclusion 

beads. Increasing the sorbent mass increases the fraction of glutamate mass 

in the sorbed phase, which decreases the biodegradation rate. However, the 



108 



RADIUS=0.05 CM 








50 7 5 

HOURS 



Figure 4-2. The impact of varying the sorption partition coefficient 
on biodegradation (L/kg) in the presence of 
aggregates with radii of 0.05 cm. (From Scow and 
Hutson, 1992). 



109 



Q 
UJ 
N 

< 
DC 
LU 
Z 



o 




HOURS 



Fiqure 4-3 Data (symbols) for aggregates with different radii and 
DSB model simulations (solid lines) of mineralization of 
50 ng 14 C-labeled glutamate/mL in the presence of gel 
exclusion beads. (From Scow and Alexander, 1992). 



110 
total fraction mineralized approaches a constant value in all cases, even though 

the observed rate of mineralization decreases with increasing sorbent mass. 

A model describing the sorption, biodegradation, and transport of 
contaminants in aggregated soils, based on rate-limited mass transfer and first- 
order biodegradation kinetics, was presented by Gamerdinger et al. (1990). 
They assumed that biodegradation occurred in both solution and sorbed 
phases. Gamerdinger et al. (1990) modeled the data reported by van 
Genuchten et al. (1989) from the column experiment with 2,4,5-trichlorophenoxy 
acetic acid herbicide in an aggregated soil. The optimized simulation that 
included degradation fit the data better than did the simulation that excluded 
degradation (Figure 4-4). The bicontinuum model with first-order degradation 
kinetics adequately described nonequilibrium sorption and biodegradation of 2- 
chloro-s-triazine herbicides in soil columns (Gamerdinger et al., 1991). 

There have been many investigations on the impact of contaminant 
sorption on biodegradation (Guerin and Boyd, 1992; Greer and Shelton, 1992). 
Often a comparison is made of contaminant biodegradation in pure cultures 
versus soil-bacterial suspensions at different mass to volume ratios. 
Understanding the sorption mechanisms and location is crucial to correctly 
interpreting experimental results. To illustrate this point, the influence of 
reversible and irreversible sorption on biodegradation will be discussed. 

Sorption of HOCs is considered to be a reversible process (Chiou et al., 
1983). Therefore, at some point in time the contaminant will be released in to 



111 



o 

c 

o 

I 

c 

CD 

o 
c 
o 
O 

S 

s 

0) 
DC 



1.00 



0.80 1 2,4,5-T 

R = 2.14 

P = 56 

0.60 



0.40 



0.20- 



0.00 




Pore Volumes (p) 



Figure 4-4. Measured and simulated BTCs for 2,4,5-T developed 
with the two region model for the two cases of no 
degradation (m=0) and degradation (/x>0). (From 
Gamerdinger et al., 1990). 



112 
the solution and become bioavailable. Therefore, biodegradation may be 

controlled by the rate of desorption, but the total amount degraded is not. This 

fact persists regardless of whether equilibrium or nonequilibrium sorption 

conditions prevail for sorption-desorption. If, however, the contaminant 

solution-phase concentration drops below the threshold concentration to 

sustain biodegradation, will biodegradation cease. 

The bicontinuum model with first-order biodegradation was used to 
evaluate desorption-limited behavior, assuming biodegradation occurred only in 
the solution phase (Figure 4-5). Input parameters (k b , mass to volume ratios, 
K p ) were obtained from experiments by Guerin and Boyd (1992). Rate 
coefficients were calculated from the k 2 -K relationship (Brusseau et al., 1989). 
An example of a case where desorption limits biodegradation of contaminants is 
presented in Figure 4-5. The total amount degraded is constant at all mass to 
volume ratios, however, biodegradation rates decreased upon increasing the 
mass of soil in the suspension. Another example of sorption decreasing 
biodegradation rates was presented by Chung et al. (1993), where the 
importance of the location of the contaminant and the microorganisms were 
incorporated into the model. Sorption occurred within interior regions of clay 
aggregates and small-diameter pores excluded microorganisms from entering 
the aggregate. Therefore, diffusion of contaminants out of the aggregates 
limited biodegradation rates although the total amount degraded was constant. 

If sorption is irreversible, as shown for diquat, the sorbed-phase 



113 




-L 



Soil: Oshtemo 
Bacteria: NP-Alk 
Mass/Volume Ratio 



0.067 

0.133 

0.2 



100 200 

Time (min) 



300 



Figure 4-5. Simulation of naphthalene degradation in soil 
suspensions. The lines were generated using the 
bicontinuum model with first order biodegradation 
kinetics, (model input parameters from Guerin and 
Boyd, 1992). 



114 
contaminant may be rendered unavailable to bacteria. Irreversible sorption 

reduces the total amount of contaminant available for degradation. This 

statement is based on the assumption that the contaminant must exist in 

solution prior to intracellular uptake. If specific interactions between the sorbent 

and the contaminant occur such as expected with quinoline (Chapter 2) and as 

demonstrated for diquat (Weber and Coble, 1968) the total amount of 

contaminant degraded will be limited by the fraction that is irreversibly sorbed. 

Figure 4-6 depicts the irreversible sorption (k 2 = 0) and biodegradation of a 

contaminant (data used from naphthalene). The decrease in the plateau value 

is indicative of sorption rendering contaminants unavailable for biodegradation. 

These examples illustrate the importance of understanding the sorption 

mechanism and how to interpret the results. 

Guerin and Boyd (1992) stated that the influence of contaminant sorption 

on biodegradation varies with the degradative microorganism in question, and 

invoked organism-specific properties to explain their results. Figure 4-7 and 4-8 

depict the sorption and biodegradation behavior of naphthalene in soil 

suspensions by the NP-Alk and the 17484 isolates, respectively. They 

concluded that the total amount and the rates of naphthalene degradation in 

soil-suspensions by two bacterial isolates were determined by whether the 

organisms had the ability to directly access sorbed-phase naphthalene. They 

suggested that NP-Alk (Figure 4-7) was judged to be effective in degrading only 

the solution-phase naphthalene subsequent to desorption. The 17484 isolate 



115 




Soil: Oshtemo 
Bacteria: NP-AIk 

Mass/Volume Ratio 



... 2 

0.2, k 2 = 



100 200 

Time (min) 



300 



Figure 4-6. Simulation using the bicontinuum model with first order 
biodegradation kinetics assuming irreversible sorption. 



116 



TIME (min) 

100 200 



300 




100 200 

TIME(min) 



300 



Figure 4-7. Naphthalene mineralization for strain NP-Alk in a soil 
free (o), Colwood (a) and Oshtemo (b) soil slurries with 
66.7 (•), 133 (□), or 200 (■) mg/mL (From Guerin and 
Boyd, 1992). 



117 



40 



30- 



20" 



10 



a 




[SOIL] 

mg/ml 
38.5 mg/ml 
76.9 mg/ml 
192 mg/ml 








100 200 

TIME (min) 



300 



Figure 4-8. Naphthalene mineralization time courses for strain 
17484 in a soil-free control and Capac (a) and 
Colwood soil suspensions (From Guerin and Boyd, 
1992). 



118 
(Figure 4-8) was thought to directly degrade sorbed-phase naphthalene. They 

concluded that naphthalene biodegradation by the NP-Alk isolate was solely 

controlled by rate-limited desorption. Based on biodegradation rates that 

appeared to exceed those estimated by assuming that degradation occurs only 

in the solution-phase, they concluded that the 17484 isolate had the ability to 

scavenge the sorbed-phase naphthalene which allowed this isolate to overcome 

desorption constraints. 

As predicted in Figure 4-5, invoking desorption-limited biodegradation is 
adequate to describe the data trends (Figure 4-8) for naphthalene mineralization 
by the 17484 isolate without assigning unique physiologic attributes to the 
microorganisms. Desorption-limited biodegradation is characterized by slower 
rates of approach to a given plateau value (i.e., constant amount degraded) as 
the mass in the system is increased. 

After reviewing their data, describing the behavior of naphthalene in the 
presence of the NP-AIk isolate (Figure 4-7) becomes more challenging than the 
typical desorption-limited degradation (Figure 4-8). Naphthalene sorption by 
organic matter of these soils likely occurs via hydrophobic partitioning in interior 
regions of the organic matter matrix. SEM photographs (Chapter 2) indicate 
that the interior sorbent regions are inaccessible to microorganisms. Therefore 
scavenging of naphthalene directly off the surface may not be possible due to 
physical constraints separating the microorganism from the contaminant. 

The kinetic data for naphthalene biodegradation by the NP-AIk isolate 



119 
appear to suggest that either sorption is practically irreversible (untenable given 

the weight of evidence of published data) or that the sorbed-phase naphthalene 

is in fact unavailable to this isolate, contrary to the conclusion reached by 

Guerin and Boyd (1992). It is also possible that the total amount of 

naphthalene degraded may be limited by low contaminant concentrations as a 

consequence of slow desorption such that the necessary enzymes for 

biodegradation are not sustained. 

The foregoing arguments should not be taken, however, to imply that 

organism-specific factors are unimportant. Even though considerable 

physiologic diversity of bacteria and other microorganisms is to be expected, 

direct surface scavenging of sorbed contaminants is yet to be unequivocally 

demonstrated. 

Microorganism-Sorbent Impacts on Biodegradation 

The constraints of contaminant-sorbent interactions on biodegradation 
has received much attention regarding bioremediation practices. However, the 
interactions of bacteria with the sorbent and the implications on biodegradation 
are not well understood. The influence of surfaces on bacteria was reviewed by 
van Loosdrecht et al. (1990). They suggested that the impact of surfaces on 
bacterial activity was not directly demonstrated but was confounded by 
secondary effects. The soil/aquifer environment is highly complex. Surfaces 
provide media for attachment and colonization of bacteria. During colonization 
bacterial activity is likely altered. Bacteria attached to particles are generally 



120 
more active than nonattached bacteria (see Griffith and Fletcher, 1991 for 

further references). Particle-associated bacteria are generally larger due to 

increased nutrient and substrate concentrations (Iriberri et al., 1987). However, 

normalizing activity on a biomass basis was suggested to alleviate such 

differences. The consequences of surfaces and variable environmental 

conditions makes extrapolation from lab-scale studies to field-scale 

bioremediation applications difficult. Much like the influence of surfaces on 

bacterial activity, the proposed influence of sorption on biodegradation is just as 

varied. 

Biodegradation of quinoline and other contaminants in soils, sediments, 
and aquifer materials is controlled by several factors (see Chapter 1). 
Conditions must be favorable to stimulate bacterial activity and biodegradation. 
For example, microbial populations require essential nutrients, carbon and 
energy sources, and electron donors or acceptors to maintain their 
physiological functions, whether a bacterial isolate degrades an organic 
contaminant aerobically or anaerobically via intracellular or extracellular 
mechanisms. Environmental factors such as oxygen content, pH, and 
temperature may also alter bacterial activity. 

In the context of this dissertation, factors important in describing the 
biodegradative behavior of quinoline by the 3N3A isolate will be addressed in 
this chapter. Oxygen content, limiting nutrients, pH, and the influence of 
surfaces in flow-through systems are factors of interest. With regard to pH, not 



121 
only will the bacterial activity potentially be altered but the sorptive capacity of 

quinoline will also be influenced (see Chapter 2). Bacterial activity in solution 

and in the presence of surfaces will be addressed. 

Quinoline Biodegradation Dynamics 

A conceptualization of quinoline biodegradation is presented in Figure 4- 
9. Quinoline degradation by a P. cepacia (3N3A) isolate occurs via membrane- 
associated dehydrogenase that forms the primary metabolite 2-HQ (Truex et al., 
1992). The second step involves ring cleavage of 2-HQ by dioxygenation and 
dehydrogenation of the benzene ring with the end product being C0 2 . Smith et 
al. (1992) reported rapid appearance of 2-HQ in solution suggesting that 2-HQ 
may be released into the solution-phase prior to intracellular uptake. Release of 
2-HQ was thought to compete with quinoline for sorption sites (McBride et al., 
1992;Smith et al., 1992). However, data presented in Chapter 2 suggested that 
2-HQ did not reduce quinoline sorption over a wide pH range (4 to 7) in batch 
systems. Alternately, sorption of 2-HQ may have blocked quinoline sorption 
sites thereby reducing quinoline sorption (McBride et al., 1992). Degradation of 
quinoline via a membrane-mediated pathway facilitates rapid degradation 
(seconds to minutes) and creates experimental difficulties when using column 
techniques. Given such constraints, McBride et al. (1992) used 1-cm long glass 
bead columns and clay-modified alumina columns with high pore-water 
velocities to facilitate monitoring quinoline sorption and biodegradation. 



122 



Clay 



/m^ 



Not Drawn to Scale 



Microorganism 




/^^s 



<^m 



Figure 4-9. Conceptualization of quinoline biodegradation in the 
presence of smectite clay minerals. 



123 
Sorption of quinoline onto a smectite clay mineral is conceptualized to 

illustrate the bioavailability of quinoline to the 3N3A isolate (Figure 4-9). 

Consider that quinoline sorption occurs onto interlamellar regions of clay 

minerals. The internal dimensions are 1 .68 nm, whereas the bacterial isolate is 

approximately 0.5 by 3 jum. Due to size constraints, the quinoline molecule 

must desorb and diffuse into the bulk solution prior to uptake and 

biodegradation. If sorption is irreversible, quinoline may be unavailable for 

intracellular biodegradation by the 3N3A isolate. It may be hypothesized that 

degradation of sorbed phase molecules (surface scavenging may occur, 

however, this behavior is unlikely for quinoline for two reasons: 1) bacteria are 

too large to enter the sorbent matrix where the majority of quinoline resides; 

and 2) formation of quinoline surface complexes on the sorbent matrix likely 

renders quinoline unavailable for biodegradation. 

In pure cultures, induction of the 3N3A isolate on 2-HQ resulted in rapid 

utilization of quinoline, indicating that the initial oxygenase reactions are 

coordinately regulated (Brockman et al., 1990). Extracellular enzymes (3N3A 

filtrate) and disrupted cells were not able to degrade quinoline. Therefore, 

quinoline enzymes cannot be induced without a quinoline transport or 

recognition function. Addition of surfactants (membrane modifier) enabled 

mutant isolates (no quinoline degradation) to subsequently degrade quinoline 

by increasing the membrane permeability. Brockman et al. (1990) suggested 

that initiation of biodegradation occurs as the result of a periplasmic binding 



124 
protein, or a cytoplasmic membrane transport protein that interacts specifically 

with quinoline. Alternately, a positively controlled regulatory protein that 

interacts with quinoline promotes induction. 

Understanding factors that influence bacterial physiology is essential for 
predicting the potential for biodegradation. The bacterial isolate, 3N3A, is a 
strict aerobe capable of utilizing quinoline as a sole source of nitrogen, carbon, 
and energy (Brockman et al., 1989). In soils, sediments, and aquifer materials, 
microsites or complete regions may be devoid of oxygen. Near-field regions of 
contaminated waste disposal sites may be depleted of oxygen as a result of 
consumption by aerobic bacteria upon biodegradation, and over time, near-field 
regions may support only anaerobic microbial communities (MacQuarrie and 
Sudicky, 1990). High contaminant concentrations may also limit microbial 
degradation due to toxic or inhibition (Truex et al., 1992). 

Localized areas supporting bacterial growth cause the development of 
bacterial biofilms (i.e., multilayer accumulation of bacterial biomass in response 
to high nutrient and substrate concentrations). Within these biofilms, microbial 
populations (species and numbers) may change in response to variations in 
oxygen and nutrient contents as the soil surface is approached. For example, 
biodegradation rates of quinoline per unit biomass of the 3N3A isolate may be 
reduced if biofilms, thus, anaerobic regions, are formed. An appropriate 
analogy may be the simple growth of a bacterial colony on an agar plate. 
Bacteria located around the perimeter of the colony are actively growing 



125 
consuming oxygen and substrate. Bacterial growth at the center of the colony 

may be substrate-limited because its separated from the source, while bacteria 

near the agar surface may be limited by oxygen that was utilized in 

transformation processes. 

In far-field regions, oxygen levels increase and contaminant 
concentrations decrease likely supporting a wide variety of microorganisms. 
The levels of oxygen necessary to support biodegradation by strict aerobes 
may vary with the particular isolate. The oxygen content required by the 3N3A 
isolate for biodegradation of quinoline is not known. 

Physical heterogeneities in aquifer materials are known to create zones 
of mixing that increase oxygen contents and provide necessary nutrients for 
bacteria (MacQuarrie and Sudicky, 1990). Increased ground water flow 
velocities and unsaturated zones increase the potential for addition of oxygen 
into porous media. Reducing the residence time within a given region by 
increasing flow velocities decreases the potential for consumption of oxygen 
and nutrients. Unsaturated zones enhance diffusion and penetration of oxygen 
in the gaseous-phase versus the solution-phase. Given that bacteria require 
oxygen, understanding the effects of pore-water velocity on oxygen 
consumption by the 3N3A isolate is essential to avoid cessation of 
biodegradation. 

Essential nutrients are required by bacteria for maintenance of simple 
physiological functions and biodegradation (Lynch, 1988). Nutrients may be 



126 
readily available in the soil solution provided the soil is rich in organic matter or 

phyllosilicate minerals which may release essential nutrients (Stotzky, 1966). If 

nutrients are unavailable (precipitated or bound), bacteria may facilitate the 

release and uptake of nutrients by excreting organic acids (Stucki et a!., 1992). 

However, oligotrophic environments (i.e., low nutrient and substrate 

concentrations), typical of deep subsurface aquifers, cause bacteria to become 

physiologically stressed and their metabolic activity reduced. Upon addition of 

substrates, enzymes must be induced to promote substrate utilization. The 

induction time (i.e., time required to produce 2-HQ) for the 3N3A isolate 

growing on quinoline in laboratory glass bead columns varied with the duration 

of starvation (i.e., physiological state of the organism) and the 

substrate/contaminant concentration. Starved cells more completely degraded 

quinoline, utilizing the substrate efficiently. In these studies, bacteria were 

primarily attached onto glass beads while quinoline remained in solution. 

Research Question and Tasks 
Many studies have been conducted to examine the influence of sorption 
on biodegradation. The following questions related to this issue are proposed 
for this chapter: 1) What processes are important in coupling sorption, 
biodegradation and transport of organic contaminants in soils, aquifers, and 
sediments? and 2) Do surfaces influence bacterial activity? To address these 
questions, miscible displacement techniques and a continuously stirred flow- 
through reactor (CSFTR) were utilized, and literature data were reassessed. 



127 
Column experiments were conducted to determine the importance of oxygen 

and nutrient contents on quinoline biodegradation. The CSFTR was designed 

to measure rapid biodegradation kinetics, and to assess the impact of surfaces 

on bacterial activity. The CSFTR has two advantages over miscible 

displacement techniques: 1) the CSFTR is completely mixed and minimizes 

physical nonequilibrium; and 2) the contaminant is rapidly monitored in the 

effluent. For column studies, at least one pore volume must be displaced 

before it is monitored in the effluent. If a contaminant is completely degraded 

prior to reaching the column outlet, simply monitoring the column effluent is not 

adequate. Unfortunately, soil columns were not sectioned to determine 

quinoline profiles throughout the columns. Hindsight reveals the limitations of 

only monitoring the quinoline behavior in the column effluent using column 

techniques. 

Material and Methods 
Sorbents 

The Norborne soil (Table 2-1) was used for the column experiments. An 
isolated particle size fraction (0.5 - 45 jum) was used for the CSFTR studies. 
This procedure increased the sorption capacity (35 cmol(-)/kg) and minimized 
the potential for migration of soil particles through the outlet filter (0.2 /xm). The 
soil was stored in suspension (10:1, liquid:solid). Prior to each experiment, the 
Norborne clay and silt suspension was equilibrated with 0.1 N CaCI 2 at the 
desired pH until the effluent pH remained constant. 



128 
Solutes 

Solutes and specific methods of analysis used in these experiments are 

listed in Chapter 2. Background matrix solutions (0.005, 0.05 M CaCI 2 ) were 

filter sterilized (0.2 /xm) to minimize biodegradation of quinoline. 

Column Studies 

The Norborne soil for bacteria-inoculated columns were inoculated (10 8 
cfu/g) and packed as described in Chapter 3. The effluent from a "sterile" 
Norborne soil column was collected for use as a nutrient media for the 3N3A 
isolate biodegradation studies. Additional FeS0 4 (2 mg/L) was added to the 
nutrient solution introduced into the soil column to enhance bacterial growth. 
Dissolved oxygen (DO) contents were varied by changing the pore- water 
velocity and monitored by a DO probe at the column outlet (see Chapter 3). 
Biodegradation was monitored (quinoline and 2-HQ) during the initial quinoline 
breakthrough and following the flow interruption. 

CSFTR 

The CSFTR (Figure 4-10) was designed to measure rapid kinetics of 
quinoline degradation, and sorption in the absence of diffusional constraints. 
The reactor consisted of a 4-mL stainless steel cylinder (Gelman Laboratories) 
with a stainless steel shaft and a teflon propeller coupled to a 200 rpm motor 
(Grainger). The shaft was supported by a stainless steel and a teflon spacer 
which contained two Buna-N-orings (McMaster-Carr) to prevent leakage. 



129 



* 




A : stainless steel shaft d 
B : Buna-N O-rings e 

C : marine type propeller f 



2 titanium 0.2 urn filters 

inlet 

outlet 



Figure 4-10. Schematic of CSFTR system used to monitor quinoline 
biodegradation. 



130 
Solutions were pumped into the inlet port with Gilson (Model 302) pump at a 

constant velocity. The outlet port consisted of a series of two 0.2 ^m titanium 

filters (Mott Metallurgical) with a glass membrane filter (1 fim) in between to 

minimize soil and bacterial biomass loss. The effluent fractions (1 to 5 min) 

were collected and analyzed by HPLC or radioassay techniques (Chapter 2). 

Soil suspensions (-1/20; 2 ml_ of a 1:10 g/mL suspension) were added to the 

reactor and the stainless steel endcap (wrapped with teflon tape) was threaded 

into place. The reactor was saturated with 0.05 M CaCI 2 in an upright position. 

Experiments were conducted under steady water flow conditions at 0.5 mL/min. 

Effluent pH was monitored periodically using an Ingold microelectrode. 

Bacterial activity in the presence of surfaces was measured by poising 
the 3N3A isolate at steady state with respect to quinoline and 2-HQ 
degradation. After steady state was reached, 2 mL of the clay suspension was 
introduced into the inlet port and the effluent was again analyzed for quinoline 
and 2-HQ. Changes in the behavior of quinoline or 2-HQ were imposed by the 
addition of the clay surfaces. Based on initial abiotic sorption studies, quinoline 
sorption at this mass to volume ratio was not measurable (R » 1) on the 
Norborne soil. 

The sorption, biodegradation, and transport of contaminants in the 
CSFTR were modeled assuming the equilibrium sorption and first-order 
biodegradation kinetics. The change in mass in the CSFTR is given as follows: 



131 
dM 



- q(C -C) - k h VC (4-1) 



at 

where M = VC + mS; V = volume of the CSFTR, m = the mass of soil, C = 
concentration in solution, C = initial concentration of the input solution, t = 
time, k b = biodegradation rate coefficient, and q = flow rate. 
The nondimensionalized equation is written as 



flf!2l - (1-C*)-YC* (4-2) 



dp 



where 



o s± m u n * C kV n qt 

V C Q q v 

Biodegradation of quinoline to 2-HQ is represented by 

%*-§ - ti-«S)-r qS (4 " 3) 

and biodegradation of 2-HQ to other metabolites given the quinoline input 
concentration based on eq 4-3 is represented by 



R m~^ - -(i+yhq)Ch Q + yqC£ (4 ' 4) 



132 
The solution assuming transient behavior of quinoline is given by 

-pO + yq) 



Rr 



1 - e nQ (4-5) 

Uq - 

1 + Yq 

Assuming steady state of quinoline sorption and biodegradation the solution 
simplifies to 

( 1+ Yq) 
The solution assuming steady state with respect to 2-HQ sorption and 
biodegradation is given by 



C' HQ - L° (4-7) 

(1 + Yq)(1+Y H q) 



Results and Discussion 
Bacterial Preparation 

The 3N3A isolate was grown and induced on quinoline and the soil 
extract (Table 4-1) to represent the soil solution in a soil/aquifer environment. 
Selection of media for the growth, cultivation, and maintenance of 
microorganisms is often defined by the intended use and the origin of the 
microorganism (Angle et al., 1991). The 3N3A isolate was isolated from « 200 
m below the soil surface in Aiken, SC. Deep aquifers are generally depleted in 
nutrients, therefore, common nutrient-rich media are not representative of the 



133 
Table 4-1 . Nutrient concentration (mg/L) extracted from the Norborne soil column. 



Ion Mg K P Zn Cu Mn Al Fe Na B Pb 



Cone 1.9 0.5 0.4 0.02 0.01 0.08 0.3 0.04 0.8 0.3 0.07 



indigenous environment. The soil effluent analysis suggested that nitrogen (not 
shown) and Fe concentrations may be limiting. However, quinoline can be 
utilized as sole source of nitrogen, and the soil likely contains sufficient amounts 
of Fe if it is continually released from the soil matrix (Zachara et al., 1988). 
Growth rates of the 3N3A isolate induced on soil column effluent were not 
quantitatively measured; however, production of pink metabolites ("dead-end" 
metabolites) and turbid cultures (10 7 cfu/mL) were produced after about 2-3 
days from use of the soil column effluent (in 0.005 M CaCI 2 ). Growth of the 
3N3A isolate on 3 g/L tryptic soy broth generated 10 9 cfu/mL within 36 hours 
suggesting that microbial populations, and ultimately biodegradation, may be 
influenced by the nutrient status in the environment. 

Consistent nutrient composition was necessary for comparison of 
biodegradation experiments; therefore, use of extracted nutrient solutions is 
recommended only if a single batch is utilized for all experiments. Bacterial 
growth notably diminished over time on various soil nutrient extracts, and did 
not produce turbid cultures or known quinoline metabolites. Therefore, the soil, 
and the nutrient solution, were likely depleted in nutrients after repeated 
washings. The nutrient solution used by Brockman et al. (1989) for inducing 
the 3N3A isolate was used in all CSFTR experiments. 



134 
Column Biodegradation Studies 

Adaptation . Adaptation of the 3N3A isolate to column conditions was 
required to promote degradation of quinoline to 2-HQ despite the fact that this 
isolate had been induced on quinoline and the soil column effluent (Figure 3-1). 
Analysis of the effluent using HPLC techniques verified that quinoline was not 
degraded in the column during the first 3.87 hours. The flow rate was 0.98 
mL/min, and the adaptation time was greater than the residence time (-11 
min). To induce degradation, a flow interruption was conducted for 13.63 hours 
and the flow was restarted at 0.195 mL/min to enhance the interaction between 
the 3N3A isolate and quinoline. After the flow interruption, 2-HQ was detected 
in the column effluent. The bacteria in these soil columns were initially induced 
on quinoline; however, after equilibration with the soil for 48 hours (during 
saturation) the 3N3A isolate required an adaptation to quinoline. This suggests 
that in soil and aquifer materials, biodegradation may be initially limited by the 
time necessary for enzyme induction. 

Truex et al. (1992) suggested that the time for bacterial induction on 
quinoline (5 mg/L) decreased from 36 to 21 hours for cells starved for 2 versus 
«70 days. Their bacterial isolate was depleted of nutrients, carbon, and energy 
sources in a saline solution for the allotted time and packed into a glassbead 
column. In this study, the 3N3A cells were added directly from the nutrient 
solution to the Norborne soil. At this time, CaCI 2 solution was introduced to 
saturate the soil column. The residual quinoline concentration introduced with 



135 
the bacterial isolate during inoculation was < 0.005 jug/g- Quinoline 

biodegradation was shown to occur at concentrations as low as 2 /xg/L (Smith 

et al., 1992). As a result, sorption likely depletes quinoline below levels required 

to sustain biodegradation in the Norborne soil columns. However, nutrients and 

other carbon sources were available in the soil solution while saturating the 

column. Bacterial activity in these soil columns is likely maintained, requiring 

only adaptation to the soil environmental conditions. The time for adaptation in 

this case was less than the 16 hours given adequate nutrient and oxygen 

contents. 

Oxygen and nutrient contents . The DO was 0.5 mg/L at a velocity of 
0.195 mL/min, and 1.91 mg/L at a velocity of 0.98 mL/min. The rate of oxygen 
consumption decreased with an increase in flow rate corresponding to the 
decreased residence time which limited oxygen consumption. At these oxygen 
concentrations, oxygen did not appear to be limiting quinoline degradation. 
However, quinoline degradation was suggested to be extremely rapid (McBride 
et al., 1992; Smith et al., 1992). Soil columns are conceptualized as a unit 
volume wherein quinoline sorption and biodegradation occurs. The outcome is 
only measured in the column effluent and does not present any information 
about the profile of oxygen or quinoline within the column. Because of the 
rapid biodegradation kinetics, quinoline may be degraded within the first 1 cm 
of the column where oxygen is plentiful. As the oxygen is limiting and the 
quinoline concentration decreases the biodegradation rates may decrease. 



136 
Biodegradation in culture suspensions ceased when the headspace of a vessel 

was purged with nitrogen to displace oxygen, verifying that biodegradation 

occurs under aerobic conditions as anticipated. From these studies, it is 

apparent that oxygen consumption is a function of the residence time within the 

soil column. However, the influence of oxygen depletion on biodegradation 

rates was not determined. A system in which oxygen content is uniform 

throughout the soil-microorganism suspension is necessary. 

A soil column that had been continuously flushed with quinoline solution 

for about 3 months (several thousand pore volumes) and was monitored 

periodically for quinoline, and 2-HQ no longer degraded quinoline. 

Biodegradation within the soil column decreased whereby only 20% of the 

quinoline introduced into the column was degraded to 2-HQ. After « 500 

additional pore volumes, quinoline biodegradation had ceased. The absence of 

N in the Norborne soil did not limit quinoline biodegradation in the soil column, 

being the 3N3A isolate utilized the N from the quinoline molecule. DO was 8 

mg/L suggesting that microorganisms may be dormant or in a resting state 

because oxygen was not being consumed. Sampling and plating the column 

effluent verified bacteria were present at about 10 5 cfu/mL Fe concentrations 

in the soil column effluent solutions were low (Table 4-1). To check for limiting 

nutrients, an FeS0 4 solution was introduced and quinoline degradation were 

monitored (Figure 4-11). Stimulation of quinoline degradation and 2-HQ 

production upon the introduction of Fe suggests that the 3N3A bacteria 



137 



O) ^ 

3 

C 

o 

1 3 

■»-« 

c 

8 2 

o 

O 



iiy 



() 
















O Quinoline 




o 


o 


• 2-Hydroxyquinoline 








- 




O 

° s 

o 


• 

It 1 1 


o 
1 


• 
I 



25 50 75 

Time (hours) 



100 



Figure 4-11. Quinoline biodegradation in a Norborne soil column 
under micronutrient limiting conditions. 



138 
deficient in Fe. However, the rate of quinoline degradation and 2-HQ 

production was much slower than in the previous studies. This suggests that 

other nutrients may be limiting or the microbial population may have been 

altered after extensive rinsing of the soil column. 

Quinoline degradation was rapid at all flow rates (0.2 to 2 mL/min) such 

that quinoline was not in the effluent from a 5 cm column after introduction of 5 

mg/L quinoline. Biodegradation was also rapid in soil columns adjusted to pH 

5. Alteration of pH may have decreased bacterial activity; however, sorption 

increased and quinoline was not detected in the column effluent. Thus, 

quinoline biodegradation kinetics could not be assessed. Altering conditions 

including dissolved oxygen and nutrient content and pH suggests that 

biodegradation occurs at high rates and efficiencies. However, this 

experimental design is not appropriate for measuring rapid quinoline 

biodegradation kinetics. To monitor rapid biodegradation rates, a CSFTR would 

facilitate rapidly monitoring quinoline in the effluent and allow for detection of 

quinoline loss over time. Therefore, a CSFTR was designed to enable detection 

of rapid quinoline biodegradation in flow-through systems. However, in cases 

where biodegradation is slower column techniques provide means of measuring 

sorption and biodegradation rates. 

CSFTR 

Biodegradation in solution. Biodegradation of quinoline was monitored to 
investigate the time required to achieve steady state and to measure the 



139 
biodegradation kinetics in bacterial suspensions (Figure 4-12). The data are 

normalized to the initial quinoline input concentration. Immediately following the 

addition of the 3N3A isolate to the CSFTR the quinoline solution was introduced 

and the effluent sampled. The quinoline and 2-HQ detected in the CSFTR 

effluent for the first 30 to 40 minutes were residual quinoline and lower 

metabolites remaining from the nutrient/induction solution. Quinoline 

biodegradation (quinoline to 2-HQ) attained steady state about 800 minutes 

after quinoline introduction. Biodegradation of 2-HQ (quinoline to 2-HQ to other 

metabolites) reached steady state in approximately the same time frame. The 

approach to steady state likely corresponds to the adaptation time and build up 

of degradative enzymes required for the 3N3A isolate in the CSFTR. The 

quinoline and 2-HQ solution concentrations were decreased to < 5 % of the 

initial feed concentration. Agitation decreases bacterial activity due to 

flocculation and damage to the cell as the stirring rate increases (Stratford and 

Wilson, 1990). However, cell disruption was shown to inactivate quinoline 

degradation (Brockman et al., 1990). Plating the internal cell suspension of 

showed 10 6 cfu/mL in the quinoline CSFTR. Agitation in a CSFTR may release 

enzymes capable of degrading; therefore, the cell suspension was filtered and 

equilibrated with quinoline and mineral salts solution. No metabolites were 

observed suggesting that quinoline degradation remains a membrane 

associated degradation process. Similarly, free enzymes (filtrates) from batch 

systems were not able to degrade quinoline (Brockman et al., 1990). This 



140 



0.8 - 



c 



g0.6 

o 
■*■< 

-o 

o 

£0.4 

03 

E 



0.2 - 















O Quinoline 




o 


o 
o 






® 2-Hydroxyquinoline 






o 












o 


o 
o 


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~ 


o 

I , 1 


o 

1 


1 


O O 
• 

° o o n 



200 



400 
Time (min) 



600 



800 



Figure 4-12. Biodegradation of quinoline and production of 2-HQ by 
the 3N3A isolate in the CSFTR. 



141 
suggested that the CSFTR is an appropriate technique for monitoring rapid 

biodegradation kinetics. Unfortunately, for every advantage of a particular 

technique, disadvantages are waiting to be discovered. After 1000 minutes, the 

CSFTR started to leak around the shaft (Figure 4-10) and the experiment was 

stopped. At this point the o-rings within the system were wearing out and the 

bacteria were potentially clogging the 0.2 /xm outlet filter. The build up in 

pressure likely caused the system to leak. 

A second CSFTR was equilibrated with the 3N3A isolate and the above 

experiment repeated (Figure 4-13). In these experiments the CSFTR was 

flushed with 0.05 M CaCI 2 to remove the excess metabolites from the 

nutrient/inoculation solution. Figure 4-1 3a verified the approach to steady state 

in the CSFTR agrees with observations in the first experiment. Steady state was 

attained in about 1500 minutes for both quinoline and 2-HQ (Figure 4-1 3a, b). 

Variations in bacterial culture conditions (length of time to introduction in the 

CSFTR) may have cause a slight change in biodegradation (Fletcher, 1986). 

Bacterial-surface interactions . Utilizing perturbation techniques 

(DiGrazia et al., 1991) facilitates evaluating the influence of a particular 
parameter in a complex system. The impact of surfaces on bacterial activity 
has long been studied. However, an increase in nutrient and substrate 
concentrations where biodegradation is limiting may confound these results. A 
perturbation of the CSFTR where bacteria were at steady state, with respect to 
quinoline and 2-HQ degradation, would provide insight into the impact of 



4 



S 3 

C 

© 

RS 
k. 

c 2 

(D 

o 

c 
o 
o 



142 



o 



S 1 # 



o 



o Quinoline 

® 2-Hydroxyquinoline 



O 



UJ 



i 



S 3 

c 
o 

*-* 

CD 

1 2 

o 

c 
o 
O 

| 1 

0) 



UJ 



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O 



Soil ( 
Introduced 



o 



o 



O.O ngOQ 



XI 




oof 



500 



1000 1500 

Time (min) 



2000 



2500 



o Quinoline 

• 2-Hydroxyquinoline 



Soil 
Introduced 



• • 



yo 



$ $ 



o 








00000)000 



XOJ 



1000 



1500 
Time (min) 



2000 



2500 



Figure 4-13. Alteration of bacterial activity upon introduction of 
Norborne clay and silt as measured by the change in 
biodegradation of quinoline. 



143 
surfaces on bacterial activity. Alteration of quinoline and 2-HQ behavior would 

indicate bacterial activity had been altered in the presence of surfaces. 

The influence of surfaces on bacterial activity (biodegradation) was 
investigated after steady state was attained for biodegradation of quinoline to 2- 
HQ to other metabolites. At 2000 and 1500 minutes (Figure 4-1 3a, b, 
respectively), 0.2 g of the Norborne silt and clay mixture was added into the 
CSFTR. Addition of surfaces in this system (small mass to volume ratio) did not 
contribute substantially to the quinoline sorption (R = 1). If quinoline sorption 
were measured at higher mass to volume ratios (R>1), diffusional constraints 
would decrease due to complete mixing of the soil and increase the fraction of 
instantaneous sorption. In Figure 4-1 3a, addition of soil initially decreased 
quinoline and 2-HQ degradation. The overall degradation of quinoline appeared 
to be reduced to about 0.3 mg/L The 2-HQ reached a concentration of 2 
mg/L followed by a decrease to 0.3 mg/L. 

In Figure 4-1 3b, the response to the addition of soil was noticeably 
different. Degradation of quinoline did not appear to be influenced by the 
addition of soil. 2-HQ degradation appeared to be reduced substantially and 
maintained a lower degradation rate. The biodegradation of quinoline to 2-HQ 
and 2-HQ to other metabolites was fit by a first-order biodegradation model 
assuming steady state conditions. The k bQ was 6.6 minutes' 1 and the k bHQ was 
0.18 minutes" 1 . 



144 
The differences between the two CSFTR experiments have yet to be 

resolved. It is possible the 500-minute delay in the addition of soil changed the 

physiological activity of the 3N3A isolate. Figure 4-1 3a suggests that the 

bacterial activity is initially altered upon addition of soil, followed by a period of 

adaptation, and approach to a new steady state. The bacterial activity may 

have been slightly reduced as a result of coverage of the bacterial isolate by 

clay particles causing decreased surface area of the bacteria. The surface area 

of the bacteria is about 1 Mm 2 /cfu. The Norborne soil has a surface area of 

about 10 m 2 /g (Zachara et al., 1988). The surface area of the soil is about 

1000 times greater that the surface area of the bacteria in the CSFTR. 

Therefore, the reduction of biodegradation due to reduced available surface 

area is plausible. 

In Figure 4-1 3b, the plateau value of 2-HQ suggests that bacteria may be 

coated with soil particles limiting intracellular uptake and subsequent 

biodegradation. Addition of the Norborne silt and clay in abiotic CSFTR 

systems did not alter the solution phase concentration of quinoline or 2-HQ at 

this mass to volume ratio. Therefore, the increase in 2-HQ was assumed to 

result from bacteria-clay interactions. Clay particles have been shown to 

adsorb onto bacterial surfaces. In this system, bacteria likely exist in discrete 

colonies with clay particles attached to their surfaces. The addition of surfaces 

did not appreciably alter the membrane-mediated degradation of quinoline. 

However, 2-HQ degradation decreased and approached a higher steady state 



145 
2-HQ concentration. Disrupted cells and cell filtrates (enzymes only) were 

incapable of degrading quinoline. Therefore, decreased activity is likely 

associated with the bacterial membrane or surface. The results suggest that 

uptake of 2-HQ into the bacterial cell was reduced. Coverage of the bacterial 

cell by clay particles may have minimized 2-HQ-bacterial contact causing the 

reduced uptake by the cell. Increased biodegradation of 2-HQ (2100 min, 

Figure 4-1 3b) may be due to the variations in the clay-bacterial associations. 

The clay particles may desorb from bacterial surfaces increasing the 

degradation rates. Alteration of bacterial activity upon addition of surfaces in 

the absence of contaminant sorption was shown to reduce the biodegradation 

rate of intracellular^ degraded quinoline metabolites. 

Summary 
The investigation of quinoline biodegradation suggested that 
microorganisms are adaptable to a variety of environmental conditions including 
pH, oxygen and nutrient contents, and flow conditions. Given adequate 
nutrients, substrates, and oxygen it is reasonable to expect that favorable 
conditions for microbial growth may be achieved in soil and aquifer 
environments. Therefore, investigating the physiological behavior of bacteria 
compatible with in situ conditions may increase the probability of successful 
bioremediation practices. From these experiments it is believed that field 
conditions may be manipulated to promote favorable conditions for 
biodegradation. 



146 
CSFTRs present a technique to investigate rapid biodegradation kinetics 

and the interaction sorption and biodegradation. At this point in time, 

improvements in the CSFrR design are necessary to fully utilize this technique. 

However, simple modifications such as working with glass vessels, larger 

sorbent particles, and slower propeller speeds may improve this technique. 

Biodegradation is likely limited by two factors in soils, aquifers, and 
sediments: 1) bacterial-sorbent associations; and 2) contaminant-sorbent 
associations. In this investigation, 2HQ biodegradation decreased upon 
introduction of soil particulates. Soil particles likely coated the bacterial surface 
reducing the available surface area, thereby reducing bacterial activity. The 
membrane-mediated biodegradation of quinoline was only slightly reduced upon 
introduction of soil particulates suggesting quinoline was able to access to the 
bacterial surface. However, due to rapid kinetics reduced biodegradation may 
not have been detected. Particle-associated bacterial activity may vary with the 
sorbent. Greater activity of particle-associated bacteria might be expected 
when sorbed onto nutrient-rich organic matter and clay mineral regions. 

The major constraint is believed to be diffusion- and desorption-limited 
biodegradation. Therefore, facilitating the release of contaminants may enhance 
bioremediation efforts. Contaminants sorbed within the interior regions of 
phyllosilicate minerals and organic matter matrices are unavailable to 
microorganisms due to size constraints. The spatial arrangement of 
microorganisms and contaminants in the soil matrix largely controls the 
potential for biodegradation. 



147 
After reviewing the literature and attempting to conduct experiments that 

require the knowledge of a chemist, microbiologist, and a physicist, the search 

for truth must take precedence over the motivation for publications. Two 

thoughts come to mind in regard to these studies. First, experimental 

techniques are crucial in investigating the impact of sorption on biodegradation. 

One must design appropriate experiments that investigate the process of 

interest and also have the scientific expertise to interpret experimental 

observations. Experimentalists must step back and appropriately interpret 

experimental observations without bias as to the expected outcome. As stated 

by Leonardo DaVinci in 1510: 

Experience does not err, it is only your judgement that errs in promising 
itself results which are not caused by your experiments. 

Second, articulation of the results must be accomplished with the utmost 

precision. When writing, it is important to choose your words carefully. 

Scientists investigating a particular topic are responsible for understanding and 

correctly utilizing the terminology of the discipline. This is particularly important 

in an interdisciplinary subject such as coupled processes. 



CHAPTER 5 
SUMMARY AND CONCLUSIONS 



Summary 



In this dissertation I investigated quinoline-soil-microorganism 
interactions: the limitations and potential of bioremediation practices. Solute- 
sorbent interactions in batch and flow-through systems were investigated to 
determine rate-limited processes controlling bioavailability of nitrogen 
heterocyclic compounds (NHCs). Microorganism-sorbent-solute interactions in 
flow-through columns were investigated to determine the impact of 
bioremediation practices on contaminant sorption and transport. Factors 
limiting bacterial growth were investigated to determine important parameters 
necessary for process coupling. Finally, a continuously stirred flow-through 
reactor was designed to measure rapid biodegradation kinetics and the impact 
of surfaces on bacterial activity. The following summary discusses the 
significance, failures, and future opportunities of this research. 

Solute-Sorbent Interactions 

Batch and column studies were conducted to investigate the sorption 
mechanisms of quinoline. A discussion of the questions proposed in the 
introduction follows: What sorption processes limit bioavailability of NHCs in 

148 



149 
remediation practices? Is the nonequilibrium sorption of NHCs accurately 

described by the bicontinuum model? 

Quinoline, a NHC, is sorbed predominately on cation exchange sites on 
clay and organic matter. As a result, sorption is dependent on quinoline 
speciation as influenced by pH. Quinoline sorption is limited by accessibility of 
sites (i.e., steric hindrances) and by the desorption-limited behavior of the 
quinoline complexes at the surface. The bicontinuum model did not 
adequately describe quinoline sorption. Rapid ion exchange likely occurs onto 
readily accessible cation exchange sites. However, reconfiguration of the 
molecule to a planar position and diffusion within the sorbent matrix is not 
adequately described. 

Sorption of quinoline within phyllosilicate minerals and organic matter 
may be impeded by initial sorption of quinoline molecules. Fixed spacing of the 
clay mineral limits the expansion beyond * 1.68 nm. Therefore, as quinoline 
molecules sorb on the outer edges of a clay mineral access to internal sites 
may be reduced. Furthermore, desorption constraints limit redistribution within 
the interlamellar regions. Sorption within organic matter is likely limited by 
specific electrostatic interactions which cause reconfiguration of the organic- 
type polymers. Both sorbents restrict migration into interior regions causing 
rate-limited sorption. 

The bioavailability of quinoline sorbed within either mineral or organic 
matrices is likely to be reduced. About 5 to 10 % of the quinoline introduced 



150 
into the soil was not recovered after extensive rinsing. This fraction was 

rendered unavailable to microorganisms based on the location of the solute and 
the microorganism. 

Microoraanism-Sorbent-Solute Interactions 

Laboratory experiments were designed to examine the sorption and 
transport of contaminants in bacterial inoculated column and batch systems. 
The objective was to assess the potential for bacteria to alter the sorption and 
transport of contaminants. Biofacilitated transport in near field regions of 
contaminated sites was of interest. The question posed was: Do 
bioremediation practices influence NHC sorption and transport? 

Lindqvist and Enfield (1992) have shown that the transport of highly 
sorptive hydrophobic organic chemicals (HOCs) (e.g, DDT and HCB) was 
facilitated by biosorption and subsequent bacterial transport. My dissertation 
showed that sorption of quinoline was reduced by interfacial biomass-induced 
speciation changes at the soil surface. Sorption may be directly decreased by 
reducing the accessibility of the sorptive regions. However, Ca sorption was 
not affected by the presence of bacterial biomass, suggesting that blockage of 
cation exchange sites was minimal. Sorption of a HOC, naphthalene, was 
slightly reduced due to a combination of processes including blockage of 
organic matter regions by hydrophilic bacteria and biofacilitated transport. 
Biofacilitated transport is likely to be greatest for hydrophobic compounds (log 
K ow > 6) in regions where high bacterial populations (10 8 cfu/mL) exist in the 
solution phase (Lindqvist and Enfield, 1992). 



151 
Near waste disposal sites, high microbial populations and colonization of 

surfaces is likely. Therefore, enhanced contaminant transport may occur either 

due to biomass-induced speciation changes of sorbent surfaces, reduced 

accessibility of the sorbent, or biofacilitated transport. Stimulation of bacterial 

growth as a result of bioremediation practices may enhance contaminant 

transport if conditions for biodegradation are not favorable. 

Solute-Microorganism Interactions 

Laboratory experiments were conducted to determine the limiting factors 
of quinoline biodegradation in flow-through column studies. The influence of 
pH, oxygen, ground water velocity and nutrients on biodegradation of quinoline 
were evaluated in flow-through systems. A CSFTR was designed to evaluate 
the rapid biodegradation kinetics of quinoline and 2-HQ given essential 
nutrients. 

Truex et al. (1992) suggested that starved (decreased physiological 
activity) quinoline degraders required about 30 hours to initiate degradation after 
being depleted of nutrients, carbon, and energy sources in batch systems. This 
study suggested that less than 16 hours were required to initiate biodegradation 
in soils that contained essential nutrients. In this case, the bacterial inoculum 
was directly added to the soil, packed into the soil column, and water flow 
initiated. The presence of nutrients and carbon sources likely sustained the 
bacterial activity and reduced the time required for induction. Conducting a flow 
interruption and a longer residence time (20 versus 10 minutes) may have also 



152 
facilitated induction by increasing the contact time between the bacteria and the 

contaminant. 

The impact of factors that may limit quinoline biodegradation, including 

oxygen, pore water velocity and pH, were not quantitatively determined in 

column experiments because of rapid quinoline biodegradation kinetics. 

However, oxygen contents decreased with a decrease in pore water velocity. 

The distribution of oxygen is not likely to be uniform throughout the soil column. 

Therefore, quinoline biodegradation was not directly determined. The 3N3A 

isolate was capable of degrading quinoline prior to reaching the column outlet 

at oxygen contents as low as 0.5 mg/L Flow interruption appeared to be 

required to induce quinoline biodegradation when pore water velocities were 

high (90 cm/hr). The soil columns at pH 6.8 and 5 indicated no difference in 

biodegradation (e.g, degradation occurred prior to reaching the column outlet). 

Microorganism-Sorbent Interactions 

A CSFTR was designed to evaluate rapid quinoline biodegradation 
kinetics and to evaluate the influence of surfaces on bacterial activity. The 
question of interest for the CSFTR experiments are: What are the 
biodegradation rates for quinoline and 2-HQ in the CSFTR? Is bacterial activity 
(i.e., biodegradation) altered in the presence of surfaces? 

A CSFTR was designed to achieve steady state growth of quinoline 
degrading microorganisms. Steady state was achieved in about 1000 minutes, 
however, due to mechanical problems the CSFTR was maintained for a 



153 
maximum of about 3000 minutes. Completely mixed reactors were verified with 

tracers (nonsorptive, nondegrading). The CSFTR supported growth of 

individual microbial colonies which are the predominant form of bacterial 

distribution in soil columns. 

The use of a CSFTR was previously demonstrated by DiGrazia et al. 
(1991). Our system varied in several ways due to requirements of the 
experiment. This system employed a 0.2 mid filter in attempt to contain the 
bacterial biomass and sorbent particles within the reactor. The CSFTR used by 
DiGrazia et al. (1991) utilized soil particles that were sieved to a fraction 
between 175 to 1000 Mm and filters that had a pore size ranging from 0.4 to 4 
Mm. This minimized soil loss, however, bacteria were not restricted from leaving 
the system. As a result they reintroduced the column effluent into the CSFTR 
once a day. Bacteria were exiting this CSFTR at about 10 5 cfu/mL despite the 
fact that 2 - 0.2 Mm filters were placed at the reactor outlet. However, steady 
state conditions were achieved with respect to bacterial growth and loss and 
quinoline biodegradation. 

The alteration of bacterial activity was observed upon the introduction of 
clay particles into the CSFTR. The impact of sorption on biodegradation results 
in decreased bacterial activity as a result in decreased uptake (blockage of the 
cell membrane) of the primary metabolite 2-hydroxyquinoline. 



154 
Conclusions 

Bioavailability 

Column studies show that the bicontinuum model does not adequately 
describe the behavior of quinoline in abiotic systems. Formation of strong 
quinoline surface complexes suggest that these complexes and quinoline sorbed 
within the interior of the sorbent matrix may be unavailable for biodegradation. 
Sorption reduces biodegradation if the contaminant is sequestered within the 
sorbent matrix. Similarly, surface complexation of quinoline reduces bacterial 
availability. 

Approaches to Bioremediation 

Contaminated sites may be prepared for bioremediation by enhancing the 
microbial consortia in the environment through fertilizer application and aeration or 
by addition of microorganisms known to degrade the contaminant of interest. 
While other processes for contaminant removal require transport from the site to 
incinerators etc., bioremediation may be done in situ. The limitations of these 
practices, however, need to be recognized to avoid delay in selecting the 
technique to remediate a site. 

Limitations that may require alternate technologies exist at sites containing 
high concentrations of contaminants and solvents that are toxic to microorganisms 
or sites that have been considerably aged. In aged sites, the contaminant likely 
resides within the interior of the sorbent and may be unavailable. 



155 
Aerobic transformation processes require the presence of oxygen for 

biodegradation. In soils, sediments, and aquifers, oxygen contents are dependent 

on the soil type and moisture content. Quinoline biodegradation occurred rapidly 

at levels as low as 0.5 mg/L In surface soils, providing adequate draining may 

facilitate oxygen diffusion and supply the required levels of oxygen for 

biodegradation. If contaminant concentrations and microbial activity are high, 

oxygen may be depleted even in well-drained soils. Land farming techniques also 

increase oxygen contents in the surface soil. However, deeper soils and aquifer 

materials may need oxygen injections or by fluctuating the water table by well draw 

down to increase oxygen mixing. 

Addition of nutrients is required to sustain growth and metabolism of 

microorganisms. The column studies suggested that after extensive leaching, 

addition of Fe increased quinoline degradation. In offshore seawater, 

biodegradation of crude oil was increased upon addition of Fe (ferric octoate) 

along with nitrogen and phosphorus. Field scale studies suggested addition of 

nutrient solutions increased biodegradation of components of fossil fuels (Pritchard 

and Costa, 1991). 

Bacterial Activity in the Sorbed- Versus Solution-Phase 

Sorption of microorganisms to sorbent surfaces was suggested to decrease 
quinoline biodegradation in systems supplied with adequate nutrients. Alteration 
of physiological functions [i.e., transport recognition functions (Brockman et al., 
1990)] likely decreased bacterial activity and reduced biodegradation. Blockage 



156 
of the cell membrane by sorbent-bacterial associations decreased 2-HQ uptake. 

More work is needed to support this experimentation on the influence of surfaces 

on bacterial activity. Direct investigation of bacterial-sorbent associations by SEM 

during sorption and biodegradation experiments would substantiate the current 

findings. 



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BIOGRAPHICAL SKETCH 

Cheryl Agnes Bellin was born in the rural community of Fairmont, 
Minnesota, on December 11, 1963. She was the last of five children that Floyd 
and Helen Bellin would bring into this world. She graduated from Fairmont High 
School in 1982 after which she attended the Minneaplois/St. Paul campus of 
the University of Minnesota and received her B.S. in agronomy with distinction 
in 1987. She received her M.S. in soil science from New Mexico State 
University in August of 1989. During the next four years she worked on her 
Ph.D. specializing in environmental chemistry and developing a desire to 
become enlightened about the complex interactions between microorganisms 
and contaminants in soils. Her next endeavor will take her to Delaware where 
she has accepted a research chemist position with DuPont in the Agricultural 
Products Division Discovery Group. 



170 



I certify that I have read this study and that in my opinion it conforms to 
acceptable standards of scholarly presentation and is fully adequate, in scope and 
quality, as a dissertation for the degree of Doctor of Philosophy. 




P. u Suresh C. Rao, Chair 
Graduate Research Professor of Soil and 
Water Science 

I certify that I have read this study and that in my opinion it conforms to 
acceptable standards of scholarly presentation and is fully adequate, in scope and 
quality, as a dissertation for the degree of Doctor of Philosophy. 





Gabriel I Bitton 
Professor of Environmental Engineering 
Sciences 

I certify that I have read this study and that in my opinion it conforms to 
acceptable standards of scholarly presentation and is fully adequate, in scope and 
quality, as a dissertation for the degree of Doctor of Philosophy. 




Kirk Hatfield 

Associate Professor of Civil Engineering 

I certify that I have read this study and that in my opinion it conforms to 
acceptable standards of scholarly presentation and is fully adequate, in scope and 
quality, as a dissertation for the degree of Doctor of Philosophy. 



P*p4&$Z* 



k- 



Peter Nkedi-Kizza 

Associate Professor of Soil and Water 
Science 



I certify that I have read this study and that in my opinion it conforms to 
acceptable standards of scholarly presentation and is fully adequate, in scope and 
quality, as a dissertation for the degree of Doctor of Philosophy. 



^A^L 



R. Dean Rhue 

Associate Professor of Soil and Water 
Science 



This dissertation was submitted to the Graduate Faculty of the College of 
Agriculture and to the Graduate School and was accepted as partial fulfillment of 
the requirements for the degree of Doctor of Philosophy. 



August, 1993 A<^ A tl ^ 

Dean, Cottage of Agriculture 




Dean, Graduate School